tag:blogger.com,1999:blog-3722233Wed, 18 Jan 2017 02:51:45 +0000typecastfocs metacommentsComputational ComplexityComputational Complexity and other fun stuff in math and computer science from Lance Fortnow and Bill Gasarchhttp://blog.computationalcomplexity.org/noreply@blogger.com (Lance Fortnow)Blogger2447125tag:blogger.com,1999:blog-3722233.post-1536965085783366798Mon, 16 Jan 2017 03:24:00 +00002017-01-15T22:25:55.708-05:00My REU program/REU's in general/Flyers? Why do some Transcripts...I run an REU program (Research Experience for Undergraduates) and I would normally urge you to urge undergrads who would benefit to apply to it and present both this link: <a href="http://www.cs.umd.edu/projects/reucaar/index.html">here</a> and this flyer: <a href="https://www.cs.umd.edu/~gasarch/BLOGPAPERS/caarflyers2017.pdf">here</a>.<br />
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I just did that. But I want to talk about REU programs, not just mine. A few points<br />
which can be construed as advise- though its more questions and what I do.<br />
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1) Do flyers still have any effect? If there is a bulletin board in a dept that is known for where to look for announcements of summer opps, then YES. Otherwise--- not sure. when I asked this question to a professor I emailed the flyer to she said that at her school they stick flyers in the bathroom stalls where they are sure to get a captive audience.<br />
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2) Should you visit schools directly? I have done this; however, most of the applicants find out about it from the NSF REU website.<br />
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3) Should students pick projects ahead of time or in the first week? When students apply they list a set of projects they want to work on (unranked but the Statement of Purpose can say which one(s) they REALLY want) so we can start on Day 1. Some of the mentors are in contact with students ahead of time. Other programs have them decide the first week. There are PROS and CONS to both.<br />
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4) How to do admissions? I do them myself since there are few enough of them (about 180 for 10 slots- though see next item) and since there are so many criteria to balance I'd rather not get into arguments with other committee members. I will sometimes (for example) say<br />
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``John, here are two people who want to work on your project. What do you think of them''<br />
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5) Of the 180 applicants about 50 do not have a statement of purpose. For me this is a deal-breaker. Either they were in the middle of applying and got another offer and took it- which is fine, but no reason for me to even look at the application, OR they have a hard time completing things and again, not worth my time. A prof once asked me `But what if they are really good''-- there are plenty of really good applicants who do fill out the statement of purpose.<br />
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6) The main activity is research but we have some social activities as well.<br />
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7) How big should teams be? We try to avoid teams of 1. We usually have teams of 2 or 3.<br />
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8) What about students from your own school? My REU grant tends to urge them to go elsewhere since the NSF likes to have people from NON-research schools, and because I personally think its better for broadening to go elsewhere. Other programs are set up differently.<br />
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9) Why do some transcript not have the name of the school on them. Drives me nuts.<br />
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In the Summer of 2017 I will be running this program for the 5th time. Feel free to leave questions about how to run one, OR your own experiences, in the comments.<br />
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http://blog.computationalcomplexity.org/2017/01/my-reu-programreus-in-generalflyers-why.htmlnoreply@blogger.com (GASARCH)2tag:blogger.com,1999:blog-3722233.post-2677209759857653054Thu, 12 Jan 2017 17:33:00 +00002017-01-12T12:33:19.617-05:00Guest Post about the first Women in Computational Topology (WinCompTop) WorkshopThe first Women in Computational Topology <a href="https://www.ima.umn.edu/2015-2016/SW8.15-19.16">WinCompTop</a> workshop was held in August at the Institute for Mathematics and its Applications (IMA) in Minneapolis, MN. In total, 27 women participated, ranging from undergraduates to full professors; in addition, five future topologists (children of the participants) attended the various social events scattered throughout the week.<br />
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The central goal of this workshop was to establish research collaborations among both junior and senior women in the field, as well as to provide an opportunity for mentoring at all levels. There were four working groups, each led by a more senior member of the community:<br />
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<a href="https://dentistry.sitecore.ualberta.ca/AboutUs/FacultyStaff/FacultyStaffCollection/GiseonHeo.aspx">Giseon Heo</a> (University of Alberta) outlined a project that extends one dimensional scale-space persistent homology (a fundamental tool in computational topology) to a pseudo-multidimensional persistence tool that can be applied to a variety of applications.<br />
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<a href="http://web.cs.ucdavis.edu/~amenta/">Nina Amenta</a> (University of California, Davis) posed a problem of producing an explicit representation of a surface S from an input point cloud P drawn from a distribution over S (possibly with some noise).<br />
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<a href="http://web.cse.ohio-state.edu/~yusu/">Yusu Wang</a> (The Ohio State University) discussed a new method of persistence-based profiles to compare metric graphs and outlined that further exploration of what information is captured by persistence-based profiles and understanding their discriminative power would be the focus of their working group.<br />
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<a href="http://www.cs.tulane.edu/~carola/">Carola Wenk</a> (Tulane University) and <a href="https://www.cs.montana.edu/brittany/">Brittany Terese Fay</a> investigated the use of topology in map construction and comparison, particularly understanding directed graphs with multiple lanes and overpasses.<br />
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The workshop began with each of the senior researchers presenting an overview of their working group’s topic. After the overview of each project, working groups began to explore their topic; over the course of the week, substantial progress was made in each group. Each working group will contribute an article to a special AWM/IMA Springer journal, co-edited by the organizers of WinCompTop 2016 (Erin Chambers, Brittany Terese Fasy, and Lori Ziegelmeier). In addition, many of the participants who attended WinCompTop will meet once again at a special session of the AWM Research Symposium in April (see <a href="https://sites.google.com/site/awmmath/home/RS17">here</a>).<br />
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The workshop also had several outings and other social events, including a poster session where over a dozen posters were presented, a panel on work-life balance, an open problem session, and several receptions or banquets. These events let participants come together as a group, establish future collaborations, and connect with one another. In addition to formally scheduled outings, informal activities such as a marshmallow roast one evening, group dinners, and many other gatherings happened throughout the week.<br />
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<i>What we (the organizers) have learned, and some questions for the community:</i><br />
How many women in Field X does it take to justify creating a “Women in X” network? (Or, more generally, an <insert-subpopulation> in X network?) This question was brought to our attention by Bill Gasarch (thanks for letting us post on your blog, BTW). We started this community as a listserv over two years ago (by the way, visit here if you’d like to join: <a href="https://groups.google.com/forum/#!forum/wincomptop/join">Here</a>. Today, we have over 100 subscribers, several of whom are not women. Regularly, opportunities are posted through this listserv, and lively discussions sometimes ensue (for example, we recently had a lengthy thread listing all of the researchers under whom one might be able to pursue a Ph.D. in computational topology). This network was started by just a handful of us who decided that there needed to be a more formal way for junior researchers to seek advice and for organizers of events to find diverse speakers. So, perhaps the answer to Bill’s question is: just a handful of people, and you’ll be surprised how quickly things grow.</insert-subpopulation><br />
<insert-subpopulation><br /></insert-subpopulation>
Acknowledgements<br />
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Finally, we want to end this post with a note of gratitude. We thank NSF,<br />
which funded the travel and local expenses for most of the participants (NSF DMS grant #1619908). We thank Microsoft Research for providing a generous donation, which funded the social events and travel for one of our international group leaders. Thanks also to AWM, which provided logistical support and advice for the event, and financial support for the upcoming follow-up events. Most enthusiastically, we thank the IMA for all of their support of both time and resources. The IMA donated the meeting spaces, breakfasts, as well as poster-printing, all in-kind. Last but not least, we thank every participant of WinCompTop 2016. We’ll see you again in 2018!<br />
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If you have any questions or comments about our experience organizing WinCompTop, we encourage you to contact us:<br />
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Erin Chambers erin.chambers@gmail.com<br />
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Brittany Terese Fasy brittany@fasy.us<br />
<insert-subpopulation></insert-subpopulation><br />
Lori Ziegelmeier lziegel1@macalester.edu<br />
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http://blog.computationalcomplexity.org/2017/01/guest-post-about-first-women-in.htmlnoreply@blogger.com (GASARCH)0tag:blogger.com,1999:blog-3722233.post-2740454628817287885Tue, 10 Jan 2017 19:27:00 +00002017-01-10T14:37:54.211-05:00Babai Strikes Back<table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody>
<tr><td style="text-align: center;"><a href="https://2.bp.blogspot.com/-pWBQD_8C61I/WHTYVOsZeWI/AAAAAAABZNw/leOuDhK9pas3R9AprOwq_27BppfapGNpgCPcB/s1600/IMG_20170109_172658.jpg" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="240" src="https://2.bp.blogspot.com/-pWBQD_8C61I/WHTYVOsZeWI/AAAAAAABZNw/leOuDhK9pas3R9AprOwq_27BppfapGNpgCPcB/s320/IMG_20170109_172658.jpg" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">"So it is quasipolynomial time again"</td></tr>
</tbody></table>
Short Version: Babai <a href="http://people.cs.uchicago.edu/~laci/update.html">fixed his proof</a>.<br />
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In November 2015 László Babai announced a talk "Graph Isomorphism in Quasipolynomial Time" at the University of Chicago, an incredible breakthrough for this important problem. The <a href="https://arxiv.org/abs/1512.03547">algorithm</a> is a tour-de-force masterpiece combining combinatorics and group theory. The result sent shock waves through the community, we <a href="http://blog.computationalcomplexity.org/2015/11/a-primer-on-graph-isomorphism.html">covered</a> <a href="http://blog.computationalcomplexity.org/2015/11/looking-forward-to-gi-result.html">the result</a> as did most everyone else, despite Babai's disclaimer that the result was not yet peer reviewed.<br />
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Robin Thomas at Georgia Tech immediately suggested we get Babai down to Atlanta to talk on the paper. Babai's dance card filled up quickly but he eventually agreed to give two talks at Georgia Tech. January 9-10, 2017, right after the Joint Mathematics Meeting in Atlanta. Robin scheduled the <a href="http://aco25.gatech.edu/">25th anniversary celebration</a> of our Algorithms, Combinatorics and Optimization PhD program around Babai's talks.<br />
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Around 4 AM last Wednesday we got a lengthy email from Babai with the subject "new development" and the first line "The GI algorithm does not run in quasipolynomial time." The email explained the new running time, still a huge breakthrough being the first subexponential time algorithm for graph isomorphism, but not as strong as before. Harald Helfgott had <a href="https://valuevar.wordpress.com/2017/01/04/graph-isomorphism-in-subexponential-time/">discovered the problem</a> while going through the proof carefully preparing for a Bourbaki seminar talk on the result. The email asked if we still wanted him to give the talk (of course we did) and instructions for removing "quasipolynomial" from his <a href="http://aco25.gatech.edu/abstracts#babai1">talk abstracts</a>. That email must have been very hard for Babai to write.<br />
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Babai posted an <a href="http://people.cs.uchicago.edu/~laci/update.html">update</a> on his home page which I too quickly <a href="https://twitter.com/fortnow/status/816628539608932356">tweeted</a>. News spread quickly in <a href="https://rjlipton.wordpress.com/2017/01/04/babais-result-still-a-breakthrough/">blog</a> <a href="https://windowsontheory.org/2017/01/05/on-expexpsqrtlog-n-algorithms/">posts</a> and by Thursday an online article in Quanta titled <a href="https://www.quantamagazine.org/20170105-graph-isomorphism-retraction/">Complexity Theory Strikes Back.</a> Scott Aaronson picked a lousy day to <a href="http://www.scottaaronson.com/blog/?p=3095">release</a> his new book-length survey on the P v NP problem.<br />
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On top of all this snow in Atlanta threatened to cancel the Monday talk. But the snow never came and Babai started his talk at 4:30 PM to a packed room. Without telling any of us beforehand, an hour earlier he had posted an <a href="http://people.cs.uchicago.edu/~laci/update.html">update</a> to his update and announced it in his talk.<br />
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<a href="https://1.bp.blogspot.com/-GoBOzMmjBZ8/WHTYVAdPtsI/AAAAAAABZNw/uBVV61KR5FwGbG0STGD_yfVg9C8pI7CcwCPcB/s1600/IMG_20170109_164434.jpg" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="201" src="https://1.bp.blogspot.com/-GoBOzMmjBZ8/WHTYVAdPtsI/AAAAAAABZNw/uBVV61KR5FwGbG0STGD_yfVg9C8pI7CcwCPcB/s320/IMG_20170109_164434.jpg" width="320" /></a></div>
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We were watching history. From the talk I <a href="https://twitter.com/fortnow/status/818575040048463872">tweeted</a> the new news though Bill Cook, also in the audience, <a href="https://twitter.com/wjcook/status/818574848016478208">beat me to the punch</a>. Babai went on to describe the issue, an error in the analysis of the running time in the recursion, and the fix, basically a way to avoid that recursive step, but I can't do it justice here. At the end he proclaimed "So it is quasipolynomial time again". And so it was.<br />
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Today Babai talked about the group theory behind the algorithm as though there was never an issue in the first place.http://blog.computationalcomplexity.org/2017/01/babai-strikes-back.htmlnoreply@blogger.com (Lance Fortnow)1tag:blogger.com,1999:blog-3722233.post-5146589104526336803Thu, 05 Jan 2017 15:09:00 +00002017-01-05T10:09:14.000-05:00Learning About Learning<div>
Yesterday Scott Aaronson released his sweeping new <a href="http://www.scottaaronson.com/papers/pnp.pdf">P v NP survey</a>. Babai gave an <a href="http://people.cs.uchicago.edu/~laci/update.html">update on graph isomorphism</a>, in short while he still has the first subexponential time algorithm for GI, he no longer claims quasipolynomial-time. We'll have more on graph isomorphism next week.<br />
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Having seen the power of neural networks for learning, how do they actually work? Over the break I decided to catch myself up. I worked through Michael Nielsen's online book <a href="http://neuralnetworksanddeeplearning.com/">Neural Networks and Deep Learning</a> chosen mainly because he co-authored one of the <a href="http://amzn.to/2iAikk5">great books on quantum computing</a> followed by the beginning of the <a href="https://www.tensorflow.org/tutorials/">TensorFlow tutorial</a>. To try out code I downloaded <a href="https://www.python.org/downloads/">Python</a> and <a href="https://www.tensorflow.org/get_started/">TensorFlow</a> and used <a href="https://www.jetbrains.com/pycharm/">PyCharm</a> as my IDE (free for academics). I should really learn <a href="https://github.com/">GitHub</a> since that holds all the code samples. Where were all these cool tools when I was a kid?</div>
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So what did I learn? Here is my high level understanding, but read the above materials to get a fuller picture. A neural network is just a weighted threshold circuit, though instead of precise threshold functions you use more continuous and differentiable functions like <a href="https://en.wikipedia.org/wiki/Sigmoid_function">sigmoid</a> or a <a href="https://en.wikipedia.org/wiki/Rectifier_(neural_networks)">rectifier</a>. If you fix the weights and biases (the negation of the threshold value), the network computes a function from input to output, for example from images of digits to the digits themselves. Typically you have a sample of labelled data and you can create an error function to see how well your network computes the solution. Fix the labelled data and now you have a new function from the weights and biases to the error.</div>
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You want to choose weights and biases to minimize the error. The general approach is gradient descent, improve a given solution by moving a small distance in the opposite direction in the gradient and repeat. I had naively thought you estimated the gradient numerically but in fact the gradient is computed symbolically using a dynamic programming-like algorithm called backpropagation based on the chain rule for partial derivatives.</div>
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Convolution nets has a special first layer that captures features of pieces of the image. Recurrent neural networks allow feedback loops.</div>
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Nielsen shows how from scratch to build and train a neural net. In TensorFlow you just design the network and then it automatically computes the gradient and has a highly optimized algorithm that can be run on GPUs or specialized hardware to minimize the error.</div>
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What caught my eye is how much of an art machine learning still is. How many nodes should you have in your network? How many levels? Too many may take too long to train and could cause overfitting. Too few and you don't have enough parameters to create the function you need.</div>
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What threshold function do you use and how to you aggregate results? Lots of various tricks to avoid overfitting and improve speed of optimization. There's no fixed procedure to choose the parameters, though you can test how well you do. So lots of trial and error to learning and experience (which I don't have) certainly helps.</div>
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So we have amazingly powerful learning tools but for now we still need humans to learn. For now.</div>
http://blog.computationalcomplexity.org/2017/01/learning-about-learning.htmlnoreply@blogger.com (Lance Fortnow)9tag:blogger.com,1999:blog-3722233.post-1335949062942238647Mon, 02 Jan 2017 19:32:00 +00002017-01-02T14:32:14.467-05:00Predictions for 2017Lance's Complexity Year in Review, posted the last week of the year (lets hope that P vs NP is not resolved on Dec 31) is a tradition that goes back to 2002. Bill posting predictions for the coming year is a tradition that goes back to 2016. Here is the last one: <a href="http://blog.computationalcomplexity.org/2016/01/predictions-of-new-year.html">here.</a> My predictions were not very good- all of those that came true were obvious (P vs NP will not be resolved, CS enrollment will go up). My biggest goof- that Hillary Clinton would beat .. Ted Cruz, by accusing him of being born in a foreign country. <br />
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However, being wrong never stopped me before, so here are my predictions for 2017<br />
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1) Some people think Trump be more presidential once he takes office. Some point to Checks and Balances in the System - but the Congress is ruled by his party. Some point to the media as a watchdog. e.g: <a href="http://www.thedailybeast.com/articles/2016/12/31/our-murrow-moment.html">here.</a> A more accurate picture is due to John Oliver <a href="https://www.youtube.com/watch?v=bq2_wSsDwkQ">here</a>. Some say Trump is a closet liberal. But I doubt his true beliefs, if he has any, matter. Its going to be bad. I second Scott Aaronson's call to not normalize this: <a href="http://www.scottaaronson.com/blog/?p=2969">here</a>.<br />
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2) Not a prediction but a thought: Prior arguments against Trump were countered with `Well Hillary is just as bad' They can't use this anymore. The following absurd conversation might happen:<br />
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NEWS: Today some democrats and John McCain questioned Donald Trumps nominee, Rex Tillerson for Sec of State, about his past dealings with Russia and Putin.<br />
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FOX NEWS: But Hillary was the worst Sec of State ever! Bengazi!<br />
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3) I will be asked to review at least one paper claiming P=NP (or P NE NP or it won't be clear what they are saying) and at least one paper claiming to determine a Ramsey or VDW number. They will be garbage. Cranks are getting into more sophisticated areas so others may be asked to look at ``solutions'' to open problems in harder areas of math. The Navier-Stokes equations (A Millennium problem, see h<a href="http://www.claymath.org/millennium-problems/navier%E2%80%93stokes-equation">ere</a>) might be a good area for cranks since they might get out some numbers and think they've solved it. I'm glad I'm not in that area.<br />
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4) Our Popular Posts links (which is determined by a program, not by us) will continue to have some of our most recent posts AND my very old post on Russell and Whitehead using 300 pages to prove 1+1=2. Why is that post seen as being so popular? I doubt it IS that popular. So--- whats going on?<br />
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5) Recall that Josh Alman and Ryan Williams showed that one method for lower bounds prob won't work <a href="http://blog.computationalcomplexity.org/2016/11/a-few-interesting-computer-science.html">her</a>e . There will be more results that rule out techniques.<br />
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6) n-person envy-free cake cutting can now be done with number-of-cuts TOW(n).<br />
There will be better upper bounds or some lower bounds on this proven this year.<br />
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7) There will be a big breakthrough on derandomization- possibly L=RL.<br />
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8) There will be a big data breach.<br />
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9) Some minor celebrity will die the last week of the year and hence not make either the<br />
`who died in 2017' lists, nor the `who died in 2018' lists. In 2016 this happened to <a href="https://en.wikipedia.org/wiki/William_Christopher">William Christopher</a>. Why do people make the `end of the year lists' before the year ends?<br />
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10) Fake News will become worse and worse. After Pizzagate there was NO apology or regret from the people who spread the false news.<br />
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11) Fake Journals, Schools, and accreditation agencies will continue to grow.http://blog.computationalcomplexity.org/2017/01/predictions-for-2017.htmlnoreply@blogger.com (GASARCH)5tag:blogger.com,1999:blog-3722233.post-5526704316780913018Thu, 29 Dec 2016 14:05:00 +00002016-12-29T09:05:11.342-05:00Complexity Year in Review 2016Paper of the year goes to <a href="http://ieee-focs.org/FOCS-2016-Papers/3933a416.pdf">A Discrete and Bounded Envy-Free Cake Cutting Protocol for Any Number of Agents</a> by Haris Aziz and Simon Mackenzie. Might not seem like a traditional complexity result but cake cutting is a computational process with a desired set of properties and this papers settles a long standing open question. Bill <a href="http://blog.computationalcomplexity.org/2016/06/there-is-now-bounded-discrete-envy-free_0.html">posted about the paper</a> back in June.<br />
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Some other nice papers from 2016: <a href="https://arxiv.org/abs/1611.05558">Hadamard not so rigid after all</a> and <a href="http://blog.computationalcomplexity.org/2016/11/a-few-interesting-computer-science.html">not usable</a> for Valiant's lower-bound program, <a href="http://eccc.hpi-web.de/report/2015/119/">2-source extractors from low-entropy sources</a> which get <a href="http://cacm.acm.org/magazines/2017/1/211100-pure-randomness-extracted-from-two-poor-sources/fulltext">near perfect randomness from two weak sources</a>, <a href="https://arxiv.org/abs/1506.04719">query complexity</a> <a href="https://arxiv.org/abs/1511.01937">separations</a>, deterministic, randomized and quantum, in two wonderful constructions <a href="http://blog.computationalcomplexity.org/2016/06/stoc-2016.html">beautifully presented at STOC</a>, <a href="https://arxiv.org/abs/1612.02788">space-efficient subset-sum</a>,and <a href="https://www.cs.sfu.ca/~kabanets/Research/natural-learning.html">learning algorithms from natural proofs</a>.<br />
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2016 will go down as a watershed year for machine learning with <a href="http://blog.computationalcomplexity.org/2016/02/go-google-go.html">AlphaGo</a>, <a href="http://www.nytimes.com/2016/12/14/magazine/the-great-ai-awakening.html">huge advances in translation</a>, <a href="https://www.tesla.com/autopilot">self-driving cars</a> and with tools like TensorFlow out in the open we'll truly see learning everywhere. Prediction didn't have such a great year with bad calls on Trump's nomination, Brexit and Trump's election. Machines learning humans still has a way to go.<br />
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We thank our guest posters <a href="http://blog.computationalcomplexity.org/2016/09/the-letter.html">Molly Fortnow</a>, <a href="http://blog.computationalcomplexity.org/2016/03/mohammadtaghi-hajiaghayi-on-david.html">MohammadTaghi HajiAghayi</a>, <a href="http://blog.computationalcomplexity.org/2016/12/guest-post-by-samir-khuller-about.html">Samir</a> <a href="http://blog.computationalcomplexity.org/2016/12/guest-post-by-samir-khuller-on-humans.html">Khuller</a> and <a href="http://blog.computationalcomplexity.org/2016/06/the-relevance-of-tcs.html">Avi Wigderson</a>.<br />
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We remember <a href="http://www.nytimes.com/2016/11/30/technology/erich-bloch-who-helped-develop-ibm-mainframe-dies-at-91.html">Erich Bloch</a>, <a href="http://www.tfs.tu-berlin.de/menue/home/team/ehrig_hartmut_prof/">Hartmut Ehrig</a>, <a href="http://www.nytimes.com/2016/12/27/movies/carrie-fisher-dead-star-wars-princess-leia.html">Carrie Fisher</a>, <a href="http://blog.computationalcomplexity.org/2016/01/rusins-freivalds-1942-2016.html">Rūsiņš Freivalds</a>, <a href="http://www.nytimes.com/2016/12/08/us/john-glenn-dies.html">John Glenn</a>, <a href="http://blog.computationalcomplexity.org/2016/03/david-johnson-1945-2016.html">David Johnson</a>, <a href="http://www.nytimes.com/2016/01/26/business/marvin-minsky-pioneer-in-artificial-intelligence-dies-at-88.html">Marvin Minsky</a>, <a href="http://cacm.acm.org/news/196208-in-memoriam-peter-naur-1928-2016/fulltext">Peter Naur</a>, <a href="http://blog.computationalcomplexity.org/2016/08/seymour-papert-1928-2016.html">Seymour Papert</a>, <a href="http://blog.computationalcomplexity.org/2016/03/hillary-putnam-passed-away-on-march-13.html">Hillary Putnam</a>, <a href="http://blog.computationalcomplexity.org/2016/03/the-value-of-shapley.html">Lloyd Shapley</a> and <a href="http://blog.computationalcomplexity.org/2016/09/boris-trakhtenbrot-1921-2016.html">Boris Trakhtenbrot</a>.<br />
<br />
As the surprises of 2016 lead us into an uncertain 2017 let me leave with my usual advice: When in a complex world, best to keep it simple.http://blog.computationalcomplexity.org/2016/12/complexity-year-in-review-2016.htmlnoreply@blogger.com (Lance Fortnow)0tag:blogger.com,1999:blog-3722233.post-1700676884503876487Mon, 26 Dec 2016 15:08:00 +00002016-12-26T10:08:35.994-05:00Hidden Figures<div class="separator" style="clear: both; text-align: center;">
<a href="https://1.bp.blogspot.com/-aY8h3AJ4Rb8/WGEpI75nJeI/AAAAAAABZCI/kkrJanZ-qrop6CBP59VbVe3saWuclUC_gCEw/s1600/Hidden%2BFigures.jpg" imageanchor="1" style="clear: left; float: left; margin-bottom: 1em; margin-right: 1em;"><img border="0" height="200" src="https://1.bp.blogspot.com/-aY8h3AJ4Rb8/WGEpI75nJeI/AAAAAAABZCI/kkrJanZ-qrop6CBP59VbVe3saWuclUC_gCEw/s200/Hidden%2BFigures.jpg" width="134" /></a></div>
Yesterday in our tradition of seeing math movies on Christmas, we saw <a href="http://www.imdb.com/title/tt4846340">Hidden Figures</a>, the story of African-American women who worked as "computers" at NASA in 1961 Virginia in the last vestiges of "separate but equal". The movie focuses on three women, Katherine Johnson, Dorothy Vaughn and Mary Jackson as they dealt with and crossed racial and gender boundaries. But this isn't just a movie you should see, rather a movie you will enjoy watching and I highly recommend it when it goes into a wide release in the US on January 6. Some minor spoilers ahead.<br />
<br />
<div>
Beyond the struggle, Hidden Figures does work as a math movie. The major storyline follows the group of mathematicians who compute the trajectories of the Mercury flights with Katherine Johnson playing a main role in figuring out how to pull John Glenn out of an elliptical orbit into a parabolic safe entry back to Earth.<br />
<br />
The movie also serves up lessons about computers. The new IBM mainframe comes and threatens the need for human computers, women (here segregated into two groups) who did the tedious manual calculations that NASA relied on. In the movie Dorothy Vaughn recognizes the threat and retrains her team to learn Fortran, perhaps a parable for how technology changes jobs today.<br />
<br />
The majority of the audience for the sold-out theater were African-American women and they laughed and cheered as the heroines of the movies succeeded. While we have made much progress in the last 50 years we still have far to go.</div>
http://blog.computationalcomplexity.org/2016/12/hidden-figures.htmlnoreply@blogger.com (Lance Fortnow)4tag:blogger.com,1999:blog-3722233.post-5946100179256928046Thu, 22 Dec 2016 15:18:00 +00002016-12-22T10:18:48.454-05:00Moneyball for AcademicsMIT and Tel Aviv business school professors Dimitris Bertsimas, Erik Brynjolfsson, Shachar Reichman and John Silberholz wrote an intriguing paper <a href="http://dx.doi.org/10.1287/opre.2015.1447" target="_blank">Tenure Analytics: Models for Predicting Research Impact</a> about using metrics in tenure decisions, <a href="https://en.wikipedia.org/wiki/Moneyball" target="_blank">Moneyball</a> for academics. The paper is behind a firewall but here is a <a href="https://papers.ssrn.com/sol3/Papers.cfm?abstract_id=2374581">preprint</a> (with the Moneyball title), an <a href="http://sloanreview.mit.edu/article/moneyball-for-professors/">essay</a> by some of the authors, and an <a href="https://www.insidehighered.com/news/2016/12/20/mit-professors-push-data-based-model-they-say-more-predictive-academics-future">article</a> from Inside Higher Ed.<br />
<br />
<a href="https://2.bp.blogspot.com/-P2A8p054hKE/WFvkGoKSZvI/AAAAAAABY90/tSnPE_GNM50HeOp8BDKJmRebDduTTHuIgCLcB/s1600/hippo.jpg" imageanchor="1" style="clear: right; float: right; margin-bottom: 1em; margin-left: 1em;"><img border="0" height="193" src="https://2.bp.blogspot.com/-P2A8p054hKE/WFvkGoKSZvI/AAAAAAABY90/tSnPE_GNM50HeOp8BDKJmRebDduTTHuIgCLcB/s200/hippo.jpg" width="200" /></a>Brynjolfsson works extensively on metric-based decision making and gave <a href="http://blog.computationalcomplexity.org/2013/04/technology-and-jobs.html">early warnings</a> on the loss of jobs to ML. I still have the HiPPO (Highest Paid Person's Opinion) from his EC 2010 invited talk. I like it for the complexity class on its back.<br />
<br />
In this article, Brynjolfsson and his co-authors use properties of the co-author and citation network graphs to predict future paper-citation based metrics, like the h-index for professors at top ranked OR departments. The paper claims that their metrics do a better prediction job than tenure committees.<br />
<br />
The IHE article captures an alternative view:<br />
<blockquote class="tr_bq">
Many professors oppose the use of bibliometrics in hiring, tenure and promotion decisions, saying that scholarly potential can’t be captured in a formula most often applied to pursuits with a bottom line, like winning games or playing the stock market. Such a system inevitably will be “gamed" by academics, critics say, and time-consuming but ground-breaking research will be sidelined in favor of “sure things” in terms of publishing -- the academic equivalent of clickbait.</blockquote>
I have a different issue--the use of bibliometrics to judge the current value of a professor. In baseball, the original Moneyball, there are measurable goals: runs, wins, championships. So you can use data analytics to both measure the current and future potential of a player. In academics, what makes a great professor? I hope the sole answer isn't the h-index. And without a subjective method to measure a successful professor, how do you train a model to predict for it?<br />
<br />
I'm not against using metrics to help with tenure and hiring decisions but I still put most of the weight on the letters.<br />
<br />
The article does talk about predicting INFORMS fellows from the network centrality model, predicting a subjecting decision from objective statistics, though doesn't compare that to tenure decisions. I wonder how well one can predict ACM Fellows as well. Another challenge here: As CS is a constantly changing field, can one use an algorithm that predicts today's fellows from 20 year old data to predict future fellows from today's data?http://blog.computationalcomplexity.org/2016/12/moneyball-for-academics.htmlnoreply@blogger.com (Lance Fortnow)2tag:blogger.com,1999:blog-3722233.post-4438251809304202082Mon, 19 Dec 2016 15:54:00 +00002016-12-19T10:56:08.223-05:00The very first Ramseyian Theorem<div>
<br /></div>
<div>
Many years ago I noticed that in several books on Ramsey Theory mention that Hilbert proved the first Ramseyian theorem. The theorem is the Hilbert Cube Lemma (HCL) which in modern language is:<br />
<br />
DEFINITION: Let x, y1, y2,...,yn be natural numbers. Then the n-cube on x, y1, y2, ..., yn is<br />
<br />
{ x+ e1*y1 + ... + en*yn : e1,...,en \in {0,1} }<br />
<br />
HCL: for all c there exists H=H(m,c) such that for all c-colorings of {1,...,H} there exists a monochromatic cube.<br />
<br />
Here are some quotes about this theorem from texts on Ramsey Theory:<br />
<br />
Graham-Rothchild-Spencer's book<i> Ramsey Theory:</i> In the middle of Szemeredi's proof of a cube lemma with double exp bounds on H (Hilbert's proof gives tower-type bounds) they write:<br />
<br />
<i>Historical Note: In 1892 D. Hilbert proved that, for any k\ge 1, if N (the naturals) is</i><br />
<i>finitely colored then there exists in one color infinitely many translates of a k-cube.</i><br />
<br />
THATS IT! No mention of WHY Hilbert proved this. According to the index this is the only mention of Hilbert in the book.<br />
<br />
From Landman and Robertson <i>Ramsey Theory over the Integers</i>:<br />
<br />
<i>The results that are generally accepted to be the earliest Ramsey-type theorems are due,</i><br />
<i>in chronological order, to Hilbert, Schur, and van der Warden.</i><br />
<br />
Later in the exercises he asks the reader to prove HCL from VDW's theorem.<br />
<br />
THATS IT! No mention of WHY Hilbert proved this According to the index this is the only<br />
mention of Hilbert in the book.<br />
<br />
Andrew Soifer's The Mathematical Coloring Book. This is a very scholarly work about the history of coloring theorems. (For my review see <a href="https://www.cs.umd.edu/~gasarch/BLOGPAPERS/soifer.pdf">here</a> .) I expected to get MORE on why Hilbert did. Soifer does devote two pages to Hilbert. But as for WHY Hilbert did it all he says is:<br />
<br />
<i>As far as we know today, the first Ramseyian-type results appeared in 1892 as a little noticed</i><br />
<i>assertion in [Hil]. Its author was the great David Hilbert. In this work Hilbert proved the </i><i>theorem of our interest merely as a tool for his study of irreducibility of rational functions.</i><br />
<i><br /></i>
I wanted to know what Hilbert proved (this was easy- I looked up the Hilbert Irreducibility<br />
theorem) and how he used his Cube Lemma to do it. I assumed this would be known and out there<br />
in English since the Hilbert Irreducibility Lemma is very important.<br />
<br />
But NO- I found the original German Version but THATS IT.<br />
<br />
Well, if you want something done, best to do it yourself. Except that I don't know German.<br />
<br />
YADDA YADDA YADDA<br />
<br />
<a href="https://arxiv.org/abs/1611.06303">Here</a> is a paper with Mark Villarino and Ken Regan, in English, that has the proof.<br />
In some later post I'll describe how the paper came about.<br />
<br />
For now I will state the Hilbert Irred Theorem, two-variable case:<br />
<br />
<br />
I<i>f f(x,t) is in Z[x,t] and is irreducible then for infinitely many natural numbers t, f(x,t) is irreducible.</i><br />
<div>
<br /></div>
<br />
<br /></div>
<div>
<br /></div>
http://blog.computationalcomplexity.org/2016/12/the-very-first-ramseyian-theorem.htmlnoreply@blogger.com (GASARCH)4tag:blogger.com,1999:blog-3722233.post-6874353303813050554Fri, 16 Dec 2016 14:49:00 +00002016-12-16T09:49:00.066-05:00Freedom of SpeechBill and I have always strongly believed in the principle of freedom of speech, guaranteed to us by the constitution of the United States. The government block speech only in extreme circumstances, fraud, libel, threats to people and property, but allows people's opinions, no matter how abhorrent we find them. <div>
<br /></div>
<div>
Speech used to be tempered by complexity. You could only talk to a small number of people at once. You had to physically print and distribute materials spouting your points of view. So while people could say what they wanted, they had some barriers to distribute that information. We believed in free speech but speech wasn't free.</div>
<div>
<br /></div>
<div>
Now with the Internet, particularly through social media, speech flows quickly and cheaply. Excitedly people could express their views easily. People also discovered that others could do so as well.</div>
<div>
<br /></div>
<div>
We should welcome this diversity of opinion, never available at this level before. We should listen to what people have to say, challenge their views and even their claimed facts, but more importantly challenge ourselves and our own viewpoints with the arguments of others. Never trust anything you see on the Internet but never be afraid of it either.</div>
<div>
<br /></div>
<div>
Instead we see calls protect people from ideas that fall significantly outside the mainstream and decide for them which facts are true or false, whether by blocking accounts or making it more difficult to distribute information. Free speech may have helped elect a president whose views and actions they find abhorrent but that's not a reason to restrict the speech. One must fight words with words, not block the words of others.</div>
<div>
<br /></div>
<div>
We must always fight for the rights of people to express themselves and avoid the path of limiting the spread of ideas. Once we start restricting the distribution of ideas we take a walk down a tough path, and someday you may find you'll have to keep your own thoughts to yourself. </div>
http://blog.computationalcomplexity.org/2016/12/freedom-of-speech.htmlnoreply@blogger.com (Lance Fortnow)11tag:blogger.com,1999:blog-3722233.post-4532920947114927319Mon, 12 Dec 2016 17:13:00 +00002016-12-12T13:14:36.298-05:00Guest post by Samir Khuller on Humans, Machines, and the Future of Work (a workshop)Guest Post from Samir Khuller on<br />
<br />
Humans, Machines, and the Future of Work<br />
(A Workshop)<br />
<br />
On Dec 5th and 6th I attended, at Rice University,<br />
a <a href="http://delange.rice.edu/conference_X/">workshop on Humans, Machines, and the Future of Work</a>.<br />
I had a wonderful lunch with John Markoff of NY Times,<br />
and Moshe Vardi of Rice University (Moshe is the brains<br />
behind this workshop).<br />
<br />
I have rarely ever attended such meetings, that are so different<br />
from the usual conferences I attend where the talks are all<br />
rather technical and half the audience is lost half way through the talk.<br />
<br />
The main theme poses the speculative question about the evolving<br />
nature of work and how technology, and especially recent<br />
advances in AI and Robotics (Self driving cars, Robots to look<br />
after the elderly, self checkout machines that can simply<br />
recognize your shopping order) can render huge categories of<br />
jobs redundant. Why hire a human, when a robot will cook<br />
dinner, and clean your home every day? What will people spend their time doing?<br />
<div>
<div>
Will the work week reduce greatly? Yet, for many, their devices and</div>
<div>
24/7 connectivity means we are working more than ever! The</div>
<div>
speakers had varied backgrounds, from Economics to Social Science</div>
<div>
to Roboticists.</div>
<div>
<br /></div>
<div>
In the end, its clear that the nature of work is constantly evolving.</div>
<div>
Our children could have job titles, our parents could never dream of</div>
<div>
when they were selecting a profession. However, the rapidly growing</div>
<div>
interest in Tech and Computing is clear - these are powerful societal</div>
<div>
forces at work. New job titles - Robot fixer, Robot Programmer,</div>
<div>
Virtual Reality Expert, Lawyer for the protection of Robots. Demand</div>
<div>
for graduates with those skills will continue to increase, and the</div>
<div>
Universities that invest quickly and early will become the dominant</div>
<div>
players. CMU, Georgia Tech and others invested very early in colleges</div>
<div>
of computing, and this has paid of handsomely for them. The demand for</div>
<div>
CS degrees is going to increase even more in the next decade</div>
<div>
with research moving more closely to the impact that technology is</div>
<div>
having on society. We as researchers, need to pay attention to</div>
<div>
societal impact, since its very real and immediate.</div>
</div>
<div>
<br /></div>
<div>
<div>
The workshop speakers were pretty amazing - talks were accessible,</div>
<div>
and extremely well delivered. I suppose such talks meant for a really</div>
<div>
broad audience (there actually were not many CS people in the audience)</div>
<div>
and thus the points being made are pretty high level.</div>
<div>
<br /></div>
<div>
I would recommend that we all become better acquainted with some of</div>
<div>
the social issues that interact with Computer Science, and going</div>
<div>
to workshops like this is a great start.</div>
</div>
http://blog.computationalcomplexity.org/2016/12/guest-post-by-samir-khuller-on-humans.htmlnoreply@blogger.com (GASARCH)4tag:blogger.com,1999:blog-3722233.post-852391936252108000Thu, 08 Dec 2016 19:39:00 +00002016-12-08T14:39:59.918-05:00Fixing the Academic Job MarketLast month I <a href="http://blog.computationalcomplexity.org/2016/11/computer-science-academic-hiring.html">posted</a> about the craziness of the computer science academic job market due mainly to the decentralized nature of our field. Here are some ideas of what we can do better. I've stolen some of these ideas from other fields such as math and economics.<br />
<br />
<b>Single Job Market System</b><br />
<br />
A single website that every CS department uses to advertise positions and accept applications. Easy for applicants to apply to multiple places and, if they wish, make their materials open for any department to see. Recommenders need only upload their letter once. We could add some additional controls, methods for applicants to indicate say geographical preferences or two-body issues.<br />
<br />
We could have an opt-in site for candidates to list where and when they have interviews. It would make coordination of job interview dates and offer timing that much simpler.<br />
<br />
<b>Annual Meeting</b><br />
<b><br /></b>
A meeting in early January that brings together all the subfields of computing so we can work as one community instead of twenty. As part of this meeting, members of recruiting committees and job candidates come and schedule short interviews with each other to make preliminary choices for on-campus interviews. CS hasn't had annual meetings since the 80's but math and econ still do.<br />
<br />
<b>Virtual Meetings</b><br />
<b><br /></b>
Every time I bring up annual meetings, people complain that we already have too many conferences in computer science. So if no physical meeting, we can set aside days to have a virtual meeting with recruiting committees and candidates talking over Skype.<br />
<br />
<b>Common Dates</b><br />
<b><br /></b>
Have some common fixed dates, just a couple of times in the spring, when departments can present offers, and when candidates must make a decision. That should reduce how long departments have to hold a position before it settles.<br />
<b><br /></b>
These last two ideas require no centralization, just willing job candidates.<br />
<b><br /></b>
<b>Job Market Paper and Video</b><br />
<b><br /></b>
As the recent <a href="http://cra.org/resources/best-practice-memos/incentivizing-quality-and-impact-evaluating-scholarship-in-hiring-tenure-and-promotion/">CRA Best Practices Memo</a> suggests, candidates should choose a single paper to highlight their research. Each candidate should also post a short (3-5 minute) video where they describe this research at a level that any computer scientist could follow. The job talk should cover this paper only, instead of trying to wow with multiple works.<br />
<br />
<b>Candidate Web Page</b><br />
<b><br /></b>
If you are publicly looking for a job, set up a web page, linked from your home page, to your job materials: CV, research statement, teaching statement, list of references, pointers to all your papers with links to PDFs, with the aforementioned job market paper and video highlighted. Also give a pointer to your Google Scholar profile page and make sure that page is correct and up to date.http://blog.computationalcomplexity.org/2016/12/fixing-academic-job-market.htmlnoreply@blogger.com (Lance Fortnow)9tag:blogger.com,1999:blog-3722233.post-5234566692235534665Tue, 06 Dec 2016 14:56:00 +00002016-12-06T15:51:33.944-05:00A students unusual proof might be a better proof<br />
<br />
I asked a student to show that between any two rationals is a rational.<br />
<br />
She did the following: if x < y are rational then take δ << y-x and rational and use x+δ<y and="" be="" delta="" let="" nbsp="" p="" rational="" such="" that="" then="" y-x=""><br />
<br />
This is correct though more complicated then what I had in mind: (x+y)/2<br />
<br />
I then asked her to prove that between two irrationals is an irrational.<br /><br />
<br />She did the following: if x < y are irrational then take δ << y-x and rational and use x+δ</y><br />
<y and="" be="" delta="" let="" nbsp="" p="" rational="" such="" that="" then="" y-x=""><br /></y>
<y and="" be="" delta="" let="" nbsp="" p="" rational="" such="" that="" then="" y-x="">SAME PROOF!</y><br />
<y and="" be="" delta="" let="" nbsp="" p="" rational="" such="" that="" then="" y-x=""><br /></y>
<y and="" be="" delta="" let="" nbsp="" p="" rational="" such="" that="" then="" y-x="">I had a different proof in mind: the number of reals in (x,y) is uncountable while the number of rationals is countable, so there must be at least one (in fact uncountable many) irrationals in (x,y).</y><br />
<y and="" be="" delta="" let="" nbsp="" p="" rational="" such="" that="" then="" y-x="">(NOTE- I originally had `the number of irrationals in (x,y) is ...' which, as comment by stu below</y><br />
<y and="" be="" delta="" let="" nbsp="" p="" rational="" such="" that="" then="" y-x="">points out, is assuming what I want to prove. Typo on my part.)</y><br />
<br />
<y and="" be="" delta="" let="" nbsp="" p="" rational="" such="" that="" then="" y-x="">These proofs raise questions about our criteria of goodness-of-proof.<br />
<br />
1) Which proof for rationals is better:</y><br />
<y and="" be="" delta="" let="" nbsp="" p="" rational="" such="" that="" then="" y-x=""><y other="" p="" pro-="" proof.="" simpler="" take="" than="" the="" x="" y=""><br /></y></y>
<y and="" be="" delta="" let="" nbsp="" p="" rational="" such="" that="" then="" y-x=""><y other="" p="" pro-="" proof.="" simpler="" take="" than="" the="" x="" y="">The delta-proof or the (x+y)/2 proof?</y></y><br />
<br />
The (x+y)/2 proof is simple, but the delta-proof also works for irrationals.<br />
<br />
<y and="" be="" delta="" let="" nbsp="" p="" rational="" such="" that="" then="" y-x=""><y other="" p="" pro-="" proof.="" simpler="" take="" than="" the="" x="" y=""><y also="" and="" delta.="" delta="" find="" for="" irrational="" p="" pro-="" rational="" take="" the="" theorem="" works="" x="" y-x="">
2) Which proof for irrationals is better:</y></y></y><br />
<y and="" be="" delta="" let="" nbsp="" p="" rational="" such="" that="" then="" y-x=""><y other="" p="" pro-="" proof.="" simpler="" take="" than="" the="" x="" y=""><y also="" and="" delta.="" delta="" find="" for="" irrational="" p="" pro-="" rational="" take="" the="" theorem="" works="" x="" y-x=""><br /></y></y></y>
<y and="" be="" delta="" let="" nbsp="" p="" rational="" such="" that="" then="" y-x=""><y other="" p="" pro-="" proof.="" simpler="" take="" than="" the="" x="" y=""><y also="" and="" delta.="" delta="" find="" for="" irrational="" p="" pro-="" rational="" take="" the="" theorem="" works="" x="" y-x="">The delta proof or the uncountable proof?</y></y></y><br />
<y and="" be="" delta="" let="" nbsp="" p="" rational="" such="" that="" then="" y-x=""><y other="" p="" pro-="" proof.="" simpler="" take="" than="" the="" x="" y=""><y also="" and="" delta.="" delta="" find="" for="" irrational="" p="" pro-="" rational="" take="" the="" theorem="" works="" x="" y-x=""><br /></y></y></y>
<y and="" be="" delta="" let="" nbsp="" p="" rational="" such="" that="" then="" y-x=""><y other="" p="" pro-="" proof.="" simpler="" take="" than="" the="" x="" y=""><y also="" and="" delta.="" delta="" find="" for="" irrational="" p="" pro-="" rational="" take="" the="" theorem="" works="" x="" y-x="">Which one is simpler?</y></y></y><br />
<y and="" be="" delta="" let="" nbsp="" p="" rational="" such="" that="" then="" y-x=""><y other="" p="" pro-="" proof.="" simpler="" take="" than="" the="" x="" y=""><y also="" and="" delta.="" delta="" find="" for="" irrational="" p="" pro-="" rational="" take="" the="" theorem="" works="" x="" y-x=""><br /></y></y></y>
<y and="" be="" delta="" let="" nbsp="" p="" rational="" such="" that="" then="" y-x=""><y other="" p="" pro-="" proof.="" simpler="" take="" than="" the="" x="" y=""><y also="" and="" delta.="" delta="" find="" for="" irrational="" p="" pro-="" rational="" take="" the="" theorem="" works="" x="" y-x="">The uncountable proof gives more information (the number of irrationals is unctble)</y></y></y><br />
<y and="" be="" delta="" let="" nbsp="" p="" rational="" such="" that="" then="" y-x=""><y other="" p="" pro-="" proof.="" simpler="" take="" than="" the="" x="" y=""><y also="" and="" delta.="" delta="" find="" for="" irrational="" p="" pro-="" rational="" take="" the="" theorem="" works="" x="" y-x="">but is nonconstructive.</y></y></y><br />
<y and="" be="" delta="" let="" nbsp="" p="" rational="" such="" that="" then="" y-x=""><y other="" p="" pro-="" proof.="" simpler="" take="" than="" the="" x="" y=""><y also="" and="" delta.="" delta="" find="" for="" irrational="" p="" pro-="" rational="" take="" the="" theorem="" works="" x="" y-x=""><y countable="" in="" irrationals="" is="" number="" of="" or="" p="" rationals="" the="" uncountable="" x="" y=""><y and="" both.="" delta.="" delta="" find="" for="" p="" pro-="" rational="" simpler="" take="" works="" x="" y-x=""><br /></y></y></y></y></y>
<y and="" be="" delta="" let="" nbsp="" p="" rational="" such="" that="" then="" y-x=""><y other="" p="" pro-="" proof.="" simpler="" take="" than="" the="" x="" y=""><y also="" and="" delta.="" delta="" find="" for="" irrational="" p="" pro-="" rational="" take="" the="" theorem="" works="" x="" y-x=""><y countable="" in="" irrationals="" is="" number="" of="" or="" p="" rationals="" the="" uncountable="" x="" y=""><y and="" both.="" delta.="" delta="" find="" for="" p="" pro-="" rational="" simpler="" take="" works="" x="" y-x="">3) Are there other proofs for either theorem?<br />
<br />
Which proof do you prefer? Why? What is your criteria?<br />
<br />
<br />
<br />
</y></y></y></y></y>http://blog.computationalcomplexity.org/2016/12/a-students-unusual-proof-might-be.htmlnoreply@blogger.com (GASARCH)14tag:blogger.com,1999:blog-3722233.post-4093420466532584480Fri, 02 Dec 2016 21:22:00 +00002016-12-04T23:40:44.030-05:00Guest post by Samir Khuller about Visiting the Simons theory Inst for ComputingGuest post by Samir Khuller on his visit to the Simons Inst. of Computing<br />
<br />
Visiting the Simons Institute for Theory of Computing<br />
<br />
A few days back I had the good fortune to spend four days at the<br />
<a href="https://simons.berkeley.edu/">Simons Theory inst.</a> at UC Berkeley (for a workshop titled<br />
<a href="https://simons.berkeley.edu/workshops/uncertainty2016-2">Learning, Algorihtm Design, and Beyond Worst Case Analysis</a>,)<br />
Not only was the workshop extremely well run, the entire Institute is<br />
amazing - from wide open spaces for collaboration to an excellent staff<br />
and amenities for visitors (especially long term visitors who have<br />
shared office space). We were missing a <a href="https://www.dagstuhl.de/en/">Dagstuhl</a> like venue in the US<br />
for a long time, and I think the Simons Theory Center partially makes<br />
up for this deficiency. Dagstuhl is of course a bit isolated, so people<br />
have no-where to go but interact, and work, and that is part<br />
of the charm. Berkeley isn’t isolated and has some of the most amazing<br />
cafes and restaurants right next to its charming campus. I ended up staying<br />
on campus at their <a href="http://www.berkeleyfacultyclub.com/">Faculty Club</a>.<br />
<br />
Simons workshops are over-subscribed and in high demand, but even on<br />
Thursday evening (my last day there) I noticed that scores of badges<br />
had not yet been picked up. Part of the problem lies in the fact that<br />
registration is free. Perhaps charging $10/day for registration will<br />
<div>
<br /></div>
<div>
<div>
ensure that people sign up for the days that they intend to be there,</div>
<div>
so others who want to attend are not locked out (to be fair, I don’t</div>
<div>
know how many were locked out, but I have the impression that due to</div>
<div>
high demand, workshops have closed registration in the past).</div>
<div>
<br /></div>
<div>
Kudos to both the Simons Institute <a href="https://iribe.cs.umd.edu/">organizers</a> as well as the ones</div>
<div>
for the special semester and workshop! I did visit Simons once in 2014,</div>
<div>
for just 15 minutes when we were visiting places to see for the design</div>
<div>
of our very own <a href="https://iribe.cs.umd.edu/">Brendan Iribe Center for Computer Science and Innovation</a>.</div>
<div>
The construction of which launched in summer 2016, and we hope to be done</div>
<div>
by August 2018. Come and visit after that! This project has consumed the</div>
<div>
last 30 months of my life.</div>
<div>
<br /></div>
<div>
One of the main benefits of attending these workshops is to see sub-fields</div>
<div>
as they form - long before new courses emerge covering these topics - and</div>
<div>
it’s inspiring to meet the leaders in our field running the</div>
<div>
program on Algorithms and Uncertainty. Finally, if you missed it,</div>
<div>
videos of talks are available online <a href="https://simons.berkeley.edu/workshops/schedule/3421">here.</a></div>
<div>
<br /></div>
</div>
http://blog.computationalcomplexity.org/2016/12/guest-post-by-samir-khuller-about.htmlnoreply@blogger.com (GASARCH)1tag:blogger.com,1999:blog-3722233.post-6730770345662627044Wed, 30 Nov 2016 21:21:00 +00002016-11-30T16:21:13.497-05:00A Few Interesting Computer Science Papers<a href="https://arxiv.org/abs/1611.05558">Probabilistic Rank and Matrix Rigidity</a> by Josh Alman and Ryan Williams<br />
<br />
Leslie Valiant outlined an approach to proving circuit lower bounds from matrix rigidity. A matrix is rigid if you need to change many entries to significantly reduce the rank. Valiant showed that one could create a function with high algebraic circuit complexity from a rigid matrix. Of course one needs a rigid matrix and the Hadamard matrices (rows are Hadamard codes) seemed the perfect candidate. Alman and Williams say not so fast, in fact the Hadamard matrices are not that rigid and won't work for Valiant's program.<br />
<br />
<a href="https://www.usenix.org/conference/osdi16/technical-sessions/presentation/hunt">Ryoan: A Distributed Sandbox for Untrusted Computation on Secret Data</a> by Tyler Hunt, Zhiting Zhu, Yuanzhong Xu, Simon Peter, and Emmett Witchel<br />
<br />
You want to use Intuit's TurboTax to prepare your taxes but you don't want to actually let Intuit or their cloud provider to see your income sources. Sounds like a job for <a href="https://en.wikipedia.org/wiki/Homomorphic_encryption">homomorphic encryption</a>, a good solution in theory but not yet practical. Ryoan, an OSDI best paper awardee, takes a systems approach to the same problem, creating a computing sandbox where one can do secure computation without allowing the cloud or software provider access.<br />
<br />
<a href="https://arxiv.org/abs/1611.04558">Google's Multilingual Neural Machine Translation System: Enabling Zero-Shot Translation</a> (and <a href="https://research.googleblog.com/2016/11/zero-shot-translation-with-googles.html">related blog post</a>) by Melvin Johnson, Mike Schuster, Quoc V. Le, Maxim Krikun, Yonghui Wu, Zhifeng Chen, Nikhil Thorat, Fernanda Viégas, Martin Wattenberg, Greg Corrado, Macduff Hughes and Jeffrey Dean<br />
<br />
Google now using a single system to translate between different pairs of languages, even pairs of languages for which it has no examples. Their analysis shows a potential internal representation of the language and the beginning of a universal translator.http://blog.computationalcomplexity.org/2016/11/a-few-interesting-computer-science.htmlnoreply@blogger.com (Lance Fortnow)0tag:blogger.com,1999:blog-3722233.post-3746110175369518274Wed, 23 Nov 2016 11:36:00 +00002016-11-23T06:36:20.844-05:00Music Theory for TheoristsI fully completed and passed my first MOOC, <a href="https://www.coursera.org/learn/edinburgh-music-theory/">Fundamentals of Music Theory</a>, a Coursera course out of the University of Edinburgh. I played the tuba in college and grad school but really just practiced scales and (usually) hit the notes. I didn't really understand keys, intervals, chords and the such and I wanted to learn.<br />
<br />
Music theory has the same problem as C++, too much overloaded notation before you really understand what's going on. So here's a quick view of music theory without the mess.<br />
<br />
Think (theoretically) of an bi-infinite sequence of notes. Every note is equivalent to notes a factor of twelve away from them (though in different octaves). Pick a note, label it 1, then the notes labelled 1, 3, 5, 6, 8, 10, 12, 1 (an octave higher) form a major scale in the key of note 1. There are twelve major scales, depending on which note you label 1. If you start at 10, i.e., 10, 12, 1, 3, 5, 6, 8, 10 you get the relative minor scale in the key of note 10. Also twelve minor scales.<br />
<br />
Start a new major scale starting from 8 you'll get 8, 10, 12, 1, 3, 5, 7, 8, just one number off from the previous scale. Repeating this process will run through all the major scales. This is called the circle of fifths (since 8 is the fifth note of the scale). You can go through the circle backwards by starting at 6.<br />
<br />
A chord is typically three or four alternating notes of a scale, for example 1, 5, 8 (the tonic) and 8, 12, 3, 6 (the dominant 7th). They can be inverted using different octaves and all sorts of other good stuff.<br />
<br />
So notation wise, there is a mapping of {A,B,C,D,E,F,G} X {Flat, Natural, Sharp} to the twelve notes with several notes getting two different names in such a way that each note of any scale can get one of the letters in cyclic order. For example the D-Major scale would be the notes D-Natural, E-Natural, F-Sharp, G-Natural, A-Natural, B-Natural, C-Sharp and back to D-Natural. You put it all together in a diagram called a musical score.<br />
<br />
Many undergrad computing courses now use Python instead of C++ to get around the notational challenges. Alas music notation goes back a millennium or so, I don't expect any changes soon.http://blog.computationalcomplexity.org/2016/11/music-theory-for-theorists.htmlnoreply@blogger.com (Lance Fortnow)11tag:blogger.com,1999:blog-3722233.post-1451981714415529103Mon, 21 Nov 2016 18:52:00 +00002016-11-21T13:52:10.341-05:00Should I tell HS students that if they do well I'll write them a letter OR do I want them to ...<br />
<br />
I teach a 3-week intense course for HS students on cryptography during the summer. Some of the students are very good, interested, and working hard. I also give out some extra credit assignments that some of them do. For such students I am glad to write letters of rec for college. I want to reward them for working hard and being interested <i>not knowing that they will get a letter for it.</i><br />
<i><br /></i>
These students don't quite know about colleges and letters and that stuff. I have two choices:<br />
<br />
1) The first day tell them that if they do well I could write a letter for them.<br />
<br />
PRO- this will encourage some of them to work harder<br />
<br />
CON- I want them to work hard and BE interested (not just SHOW interest, though I doubt they are that good as actors) NOT because of some reward but because they really are interested. Contrast:<br />
<br />
<i>Bob showed an intense interest in computer science</i><br />
<i><br /></i>
<i>to</i><br />
<i><br /></i>
<i>Bob showed an intense interest in computer science but it may have been just for show to get this letter. Gee, I can't tell.</i><br />
<i><br /></i>
2) Don't tell them. This way when they work hard and show interest its more likely genuine.<br />
<br />
PRO- as noted, their behavior is genuine<br />
<br />
CON- They may not work as hard.<br />
<br />
I tend to do (1) now- tell them. One thing, don't tell them too much and make it simple. I used to say that I would write a letter even for a B student if there were extenuating circumstances or if I could tell they really were good and just happened to blow an exam, or something like that. But this just invites more questions about what they need to get a letter, and I've never had one of those cases where a B-student is better than he looks. (This could be because my exams are of the type where there is no time pressure as evidenced by half the students leaving about half way through. They are not easy, but they depend on knowledge not cleverness, so more time does not help. Or it could be something else about my teaching and grading.)<br />
<br />
So- better to tell them about a letter option or not?<br />
<br />
<br />
<br />
<br />http://blog.computationalcomplexity.org/2016/11/should-i-tell-hs-students-that-if-they.htmlnoreply@blogger.com (GASARCH)5tag:blogger.com,1999:blog-3722233.post-3514400494201116163Thu, 17 Nov 2016 13:52:00 +00002016-12-08T14:40:38.837-05:00Computer Science Academic HiringMy faculty recruiting season in 2016 never stopped. The spring recruiting season bled through summer right into various fall recruiting activities. How I envy my friends in other fields whose faculty recruiting season runs in less than three months.<br />
<br />
Economist Noah Smith writes <a href="http://noahpinionblog.blogspot.com/2012/02/how-i-survived-economics-job-market.html">about the process</a> he went through in the econ job market in 2012.<br />
<blockquote class="tr_bq">
After applications go out, employers contact grad students for interviews. These interviews take place at the AEA's Annual Meeting in early January, which is a gigantic confab where most of the economists in the country go to eat free food and hobnob. As an interviewee, you generally don't have time to go to any of the presentations or speeches; you're running back and forth from hotel to hotel, going to interview after interview. This year's AEA Meeting was in Chicago. </blockquote>
<blockquote class="tr_bq">
You then wait a week or two, and the employers who are interested in you call you back and schedule a flyout. Flyouts, which happen in February and March, involve going to the place, meeting the people, getting taken to dinner, and presenting your research. After that, offers go out.</blockquote>
Ahh to be done with recruiting before April Fools Day. Why can't we do this in Computer Science? In one word: Decentralization.<br />
<br />
Academic fields act administratively like their field. So econ creates a structured market with the goal of an efficient (in their sense of the right people get the right jobs) outcome.<br />
<br />
Computer science abhors centralized control. We lack a strong central authority and have very little coordination between different departments. So we have a process that takes a long time to work its way through and quite often fails to get that efficient outcome. Even the CRA's <a href="http://archive2.cra.org//uploads/documents/events/snowbird/2010slides/HiringCRASnowbird2010.pdf">modest 2010 proposal</a> for some common earlier deadlines went nowhere.<br />
<br />
What can we do? I welcome suggestions and will give some of my own in a <a href="http://blog.computationalcomplexity.org/2016/12/fixing-academic-job-market.html">future post</a>.http://blog.computationalcomplexity.org/2016/11/computer-science-academic-hiring.htmlnoreply@blogger.com (Lance Fortnow)6tag:blogger.com,1999:blog-3722233.post-2083749396534958072Mon, 14 Nov 2016 03:36:00 +00002016-11-13T22:36:20.521-05:00Did you do research when you were an undergrad? Well.. it was a different time.<br />
Dan is a high school student who has worked with me and is now an ugrad at College Park<br />
<br />
DAN: Bill, did you do research when you were in high school?<br />
<br />
BILL: No, things were different then, there wasn't really a mechanism for it. Or, as you young people would say, it wasn't a thing.<br />
<br />
DAN: When as an undergrad did you begin to do research?<br />
<br />
BILL: Well, I never did research as an ugrad either.<br />
<br />
DAN: Then how did you get into Harvard? Did they accidentally put your folder in the wrong pile?<br />
<br />
BILL: Good question. I'll ask my adviser if he recalls what went wrong back in 1980.<br />
<br />
DAN: Really? You'll ask him?<br />
<br />
BILL: NO!<br />
<br />
Okay, the real question here is:<br />
<br />
At some point (before 1980) doing research at an ugrad in college was not really a thing many people did.<br />
<br />
And now its quite common.<br />
<br />
What changed? Is the change for the good? I'll phrase my thoughts and questions in the form of a question (the opposite of Jeopardy).<br />
<br />
1) Are there more magnet schools and more ways to funnel students into research early?<br />
<br />
2) Do computers allow students to to more research than they could have back before (say) 1980?<br />
<br />
3) Is the phrase `HS research' a bit odd- it is more learning then doing?<br />
<br />
4) Is there a cycle going on- since more students are doing research, more have to do research to keep up in order to get into grad school? Is this even an issue for college admissions and/or scholarships?<br />
<br />
5) Has the quality of research at HS science competitions increased ? Ugrad research? Grad student research? Prof research?<br />
<br />
6) Does having HS or ugrads do research with you increase or decrease your productivity? (That depends on the students of course)<br />
<br />
7) Do colleges give faculty kudos for guiding HS or ugrad research? (That depends on the school of course)<br />
<br />
8) Are there more grants for ugrad research then before 1980? Are REU programs fairly new?<br />
<br />
9) Does an ugrad now NEED to have done research to get into one of the top X grad schools? If so is this a good thing or not? Does this hurt those without the oppurtunity to do research? Do REU programs help alleviate this problem?<br />
<br />
10) Are students entering grad school knowing far more than they used to?<br />
<br />
11) Some magnet schools REQUIRE HS students to do research. Is this a good thing?<br />
<br />
12) I've been using 1980 as a reference for no good reason- when did HS research and ugrad research increase? Was it gradual or was there some big increase over some X years where X is small?<br />
<br />
<br />
<br />http://blog.computationalcomplexity.org/2016/11/did-you-do-research-when-you-were.htmlnoreply@blogger.com (GASARCH)3tag:blogger.com,1999:blog-3722233.post-6699424249638316255Thu, 10 Nov 2016 19:52:00 +00002016-11-10T14:52:29.850-05:00Our Role and ResponsibilityIt's Trump but not just Trump. Brexit. Right-wing politicians gaining power in France, Netherlands, Austria and beyond. We worry about the future of our country and the whole world at large.<div>
<br /></div>
<div>
<div>
But what role have we played? By we I mean those of us who work in technology-related fields and have benefited the most from the new economy. </div>
<div>
<br /></div>
<div>
There's a large population who's lives haven't gotten better. Not just the poor, we're talking the lower 80% of the economy. Our changing economy hasn't greatly improved the life of the middle class. </div>
<div>
<div>
<br /></div>
<div>
Our technologies have put people out of jobs. We tell them our technology will create more and better jobs, our own version of trickle-down economics. They just need to learn what we have created, drive our Ubers, at least until the Ubers can drive themselves. </div>
<div>
<br /></div>
<div>
We love working at universities where we can educate the very top students. But many don't get the opportunity to go to college at all. They are honest people willing to work hard and not seeing their lives improving. And we just call them "uneducated". </div>
<div>
<br /></div>
<div>
We have learned how to mine data but often forget the people behind the data and get caught by surprise when things don't go the way we expected from the data.</div>
<div>
<br /></div>
<div>
We've created new communication channels. But we also control those channels. We often make the choices between usability, security, privacy, fairness, free speech and preventing hatred and discrimination. But who are we to make those choices. They have little say.</div>
<div>
<br /></div>
<div>
Who are they? They are us, fellow Americans. We need to make sure that all of us benefit from our changing world and everyone feels that they contribute to making it better and everyone has a say. Democracy, messy as it is, means that if people don't feel they the world looks out for them, they will find someone who promises change no matter the baggage they carry. And we need to listen or we end up with Donald Trump.</div>
</div>
</div>
http://blog.computationalcomplexity.org/2016/11/our-role-and-responsibility.htmlnoreply@blogger.com (Lance Fortnow)20tag:blogger.com,1999:blog-3722233.post-2475576180342356228Mon, 07 Nov 2016 12:00:00 +00002016-11-07T16:48:25.635-05:00And the winner is... HarambeTomorow is the Election for Prez of the USA! This post is non-partisan but, in the interest of full disclosure, I state my politics: I will be voting for Hillary Clinton. I urge you to read the posts by Scott Aaronson: <a href="http://www.scottaaronson.com/blog/?p=2777">here</a> and by Terry Tao <a href="https://terrytao.wordpress.com/2016/06/04/it-ought-to-be-common-knowledge-that-donald-trump-is-not-fit-for-the-presidency-of-the-united-states-of-america/">here</a> or John Oliver's segment <a href="https://www.youtube.com/watch?v=DnpO_RTSNmQ">here</a> to see why. I would have thought that 99% of their readers, and mine, are voting for Clinton, but looking at the comments on Scott's an Terry's blog I realize that might not be true. (ADDED LATER- A nice article that summarizes the entire election, I put it here for you and for me: <a href="http://www.thedailybeast.com/articles/2016/11/07/50-moments-that-defined-the-2016-election-cycle.html">here</a>)<br />
<br />
However, I am not blogging about who you should vote for.<br />
<br />
I had the teachers of Discrete Math and Algorithms (two diff courses) give their students paper ballots with the four candidates on the Maryland ballot (Clinton, Trump, Johnson, Stein, write-in) and had them vote. But with a difference:<br />
<br />
Discrete Math did the standard voting where you vote for ONE candidate<br />
<br />
Algorithms did approval voting- where you mark all those you approve of.<br />
<br />
DISCRETE MATH RESULTS: 428 students.<br />
Clinton: 305<br />
Trump: 44<br />
Johnson:21<br />
Stein:11:<br />
Abstain (or some variant like `f**k all of them')-7<br />
Sanders-6<br />
Harambe. The Gorilla who was shot (see <a href="https://en.wikipedia.org/wiki/Killing_of_Harambe">here</a>)-3<br />
Hugh Mungus (word play - you figure it out. Also see <a href="https://www.youtube.com/watch?v=yCJiblUJl4g">here</a>)-3<br />
Ken Bone (he asked a good question at the Town Hall Debate. Then...)-2<br />
Vermin Supreme (Policy: All Americans must brush their teeth. See <a href="https://en.wikipedia.org/wiki/Vermin_Supreme">here</a>)-2<br />
Joe Yecco (don't know who it is. Maybe a student in the class) -2<br />
<br />
For the people who got 1 vote see <a href="http://www.cs.umd.edu/~gasarch/BLOGPAPERS/jasonone">here</a>. There were 22 of these.<br />
<br />
ALGORITHMS RESULTS. 251 students (won't add up since its approval voting)<br />
Clinton-155<br />
Johnson-63<br />
Stein-59<br />
Trump-40<br />
Sanders-18<br />
Abstain-14<br />
Clyde Kruskal (who teaches the course)-13<br />
Tom Reinhart (a CS lecturer at UMCP)-5<br />
Larry Herman (a CS lecturer at UMCP)-3<br />
John Kasich-3<br />
Evan McMullen (Third Party Candidate who is doing well in Utah)-3 See <a href="https://en.wikipedia.org/wiki/Evan_McMullin">here</a><br />
Vernin Supreme (see above)-3<br />
Harambe the Gorilla (really!) -2<br />
Michelle Obama-2<br />
Eric Sim (don't know who this is- Maybe a student in the class)-2<br />
<br />
For people who got 1 vote see <a href="http://www.cs.umd.edu/~gasarch/BLOGPAPERS/clydeone">here</a><br />
<br />
For more complete information see <a href="http://www.cs.umd.edu/~gasarch/BLOGPAPERS/electionclydecomplete">here</a><br />
<br />
What to make of all of this?<br />
<br />
College Students are largely Liberal so the pro-Clinton vote is not surprising. Also Maryland is a strongly democratic state, though I think being a college is more of a factor than being in Maryland. I suspect that students at UT Austin are also liberal even though the state isn't.<br />
<br />
I've had large classes vote before, but not by approval voting. Both of the classes above had more write-ins than usual- though that is less surprising for approval voting.<br />
<br />
Approval voting shows that Trump is very few people's second choice. That is, those that don't like him REALLY don't like him. Again, this is among the narrow demographic of college students taking Algorithms at UMCP CS.<br />
<br />
Any odd candidate who gets ONE vote does not surprise me. If ONE person votes for Aliko Dangote, a real (see <a href="https://en.wikipedia.org/wiki/Aliko_Dangote">here</a>) Nigerian Billionaire (he has NOT emailed you) that is not surprising.<br />
<br />
If someone who is sort-of out there get TWO or more votes (Vernin Supreme, Hugh Mungus) I am not surprised. Those two have websites and a following, though small.<br />
<br />
The three votes for Harambe the Gorilla surprised me. I've looked on the web, and this is NOT a thing- there is no Harmabe for Prez websites, even as a joke (I assume if they existed they would be a joke). So I am surprised he got 3 votes in DM and 2 vote in Algorithms. One of those voted for Clinton, Johnson, Stein, and Harambe. I'm assuming that's a strong anti-trump vote.<br />
<br />
Does this poll have any predictive value? The winner of the Discrete Math Poll ended up being the real winner in 1992, 1996 (though there were more Ross Perot Votes then I would have thought),<br />
2008, and 2012. Note that in all these cases the democratic candidate won. Not a surprise.<br />
<br />
Some personal opinions:<br />
<br />
1) If Trump loses what will the republicans learn from this. NOTHING since Trump was such an odd candidate. I wish it would have been Hillary (or someone like her) vs Cruz (or someone on the hard right) so that if they lose the reps can't say, as some have, <i>we lost because we weren't conservative enough.</i> And one can hope that Hillary vs Cruz would have more of a contest of ideas.<br />
<br />
2) I'm not sure what would be better for the Rep Party- a Trump loss or a Trump win.<br />
<br />
3) Predictwise says a Hillary win is around 85% likely. Nate (the only pollster known by his first name!) says 65%. If Hillary wins it won't be clear who was right? If Trump wins then Nate would have been more right, but not sure what that means. More generally:<br />
<br />
If two people give different predictions, in the end you can see who was right<br />
<br />
If two people give different probabilities of an event, then its harder to see who was right.<br />
<br />
<br />
<br />
<br />
<br />
<br />
<br />http://blog.computationalcomplexity.org/2016/11/and-winner-is-harambe.htmlnoreply@blogger.com (GASARCH)3tag:blogger.com,1999:blog-3722233.post-7471165882130638832Thu, 03 Nov 2016 18:10:00 +00002016-11-03T14:10:17.897-04:00Do We Still Need Great Minds?An <a href="http://blog.computationalcomplexity.org/2016/10/alternate-histories.html?showComment=1477043660292#c1928303853197391087">anonymous comment</a> on a <a href="http://blog.computationalcomplexity.org/2016/10/alternate-histories.html">recent post</a> on alternate histories.<br />
<blockquote class="tr_bq">
As far as science is concerned I don't believe that the great minds are needed anymore. They only speed things up that would later have been developed by an industry of a great mass of brilliant but more mediocre researchers. The best examples are Godel's and Turing's work which would have been done necessarily by the next generation of logicians or theoretical computer scientists. Regarding your own contributions it is fair to say that "the future doesn't need you." Anything important would also be created sooner or later by others, only some idiosyncratic work of minor importance could be left undone forever.</blockquote>
Depressing. So we do either mediocre work or work that others would later do anyway.<br />
<br />
Of course we can never know. We can't tell if some great idea today may not have existed if a single genius didn't create it. We also don't know what technology we don't have because of someone who became a playwright instead of a scientist. <br />
<br />
I don't doubt we'd have the P v NP question without Cook, Karp and Levin, though our understanding of the problem would have a very different flavor.<br />
<br />
Take someone like Manuel Blum. Through him and his students we got formal models of cryptography that led to zero-knowledge proofs, interactive proofs, probabilistically checkable proofs, lower bounds on approximation and major advances in coding theory, among so much more. Would we have all this work if Manuel never existed? Maybe, eventually, but we'd live in a whole different theory world without him. And that world would always look different until we find a new Manuel to unify it.http://blog.computationalcomplexity.org/2016/11/do-we-still-need-great-minds.htmlnoreply@blogger.com (Lance Fortnow)7tag:blogger.com,1999:blog-3722233.post-4433906846483157736Tue, 01 Nov 2016 01:33:00 +00002016-11-01T13:52:28.486-04:00My chair wants me to post about.. Mohammad Haj wants me to post about.. I want to post about...Maryland is looking to hire lecturers and my chai Samir wants me to post it on my blog. I think he overestimates the power of the blog, however, <a href="https://www.cs.umd.edu/job/2016/lecturersenior-lecturer-position">here</a> is the link. I could use this to launch into a post about either the value of lecturers or how to handle the fact that CS enrollment is so high, but I've already posted on those in the past: <a href="http://blog.computationalcomplexity.org/2014/02/maryland-looking-for-lecturerwho.html">here</a> and <a href="http://blog.computationalcomplexity.org/2015/08/ways-to-deal-with-growing-number-of-cs.html">here.</a> (ADD- Actually my chair wanted me to post on all of our hiring which also includes professors, so see <a href="https://www.cs.umd.edu/about/employment/all">here</a>)<br />
<br />
Mohammad Hajiaghayi is the Program chair of the SPAA conference and wants me to post it on my blog. I think he overestimates the power of the blog, however <a href="http://spaa.acm.org/">here</a> is the link. I could use this to launch into a post about the prestige-conference model of academia, or other conference issues, or parallelism, but these topics have also already appeared on the blog, mostly by Lance.<br />
<br />
<br />
But here is the real question: Is it easier or harder to get information (e.g., UMCP CS is looking for a lecturer, SPAA call for papers is out) than it used to be.<br />
<br />
EASIER: We have so many different mechanisms. Blogs, email, FACEBOOK, Twitter. Conferences used to have posters as well- I don't think I"ve seen one for a while. (If someone knows where some of the<br />
old posters are, on line, please leave a comment- some of them were real neat!).<br />
<br />
HARDER: we all get too much email (for those still on email), and get too much input in general. Hence things can get lost. I'm on so many mailing lists for talks that I actually MISS talks I want to goto since I tend to ignore ALL of those emails.<br />
<br />
If you WANT to find something out, is that easier. If you want to find out<br />
<br />
<i>when is the SPAA conference</i><br />
<i><br /></i>
yes- you can Google it.<br />
<br />
For something like<br />
<br />
<i>what schools are advertising they want to hire a lecturer?</i><br />
<i><br /></i>
prob yes though I am not quite sure where to look.<br />
<br />
There are things out there that if you knew about them you would want to know, but you are not quite sure how to look. Do we come across them more or less than we used to. I think more since, at least in my case, people I know email me stuff they think I will care about and they are usually right (Ramsey Theory, Cake Cutting papers, and satires of Nobel Laureate Bob Dylan find there way to my inbox.)<br />
<br />
<br />http://blog.computationalcomplexity.org/2016/10/my-chair-wants-me-to-post-about.htmlnoreply@blogger.com (GASARCH)1tag:blogger.com,1999:blog-3722233.post-8959717745839330927Thu, 27 Oct 2016 11:29:00 +00002016-10-27T07:29:49.325-04:00Get ReadyMy daughters, now in college, never knew a time when they couldn't communicate with anyone instantaneously. Molly, now 18, takes pride having the same birth year as Google. They have never in their memory seen a true technological change that so dramatically affects the world they live in. But they are about to.<br />
<br />
The 50's and 60's saw a transportation revolution. The Interstate highway system made local and national car and truck travel feasible. The jet engine allowed short trips to faraway places. The shipping container made transporting a good, made anywhere in the world, cheaper than producing it.<br />
<div>
<br />
We could have national and worldwide academic conferences. China became a superpower by shipping us low-cost goods. Dock worker jobs, the kind held by Archie Bunker, have morphed and shrunk, even as the number of imported goods has grown.<br />
<br />
In the 90's we had a communications revolution. The cell phone kept us connected all the time. The home computer and the Internet gave us immediate access to the world's information and Google helped us sort through it.<br />
<br />
It fundamentally changed how we interacted. No longer did we need to make plans in advance. Eventually we would have little need for encyclopedias, almanacs, maps, or physical media for music, photos and movies. Not to mention new types of companies and the transformation of how businesses could work with their employees and contractors spread across the world.<br />
<br />
That brings us to today. We are at the brink, if it hasn't already started, of an intelligence revolution, the combination of big data, machine learning and automation. The initial obvious transformation will come from autonomous cars, which will change not only how we get from point A to point B but how we plan roads, businesses and where we live. Beyond that work itself will change as we will continue to automate an ever growing number of white collar jobs. As with every transformation, the world we live in will change in unforeseen ways, hopefully more good than bad.<br />
<br />
I really look forward to watching these changes through my daughter's eyes, to see how this new society directly affects them as they start their working lives. And how their children will one day see an old-fashioned automobile with relics like foot pedals and a steering wheel and be shocked that their parents once drove cars themselves.</div>
http://blog.computationalcomplexity.org/2016/10/get-ready.htmlnoreply@blogger.com (Lance Fortnow)5tag:blogger.com,1999:blog-3722233.post-2044265367280232313Mon, 24 Oct 2016 22:20:00 +00002016-10-24T18:20:42.832-04:00Exaggeration is one thing but this is....<a href="http://www.storyofmathematics.com/mathematicians.html">This</a> website is about the history of math and lists famous mathematicians. The ones from the 20th century are biased towards logic, but you should go there yourself and see who you think they left out.<br />
<br />
There entry on Paul Cohen is... odd. Its <a href="http://www.storyofmathematics.com/20th_cohen.html">here</a>. I quote from it:<br />
<br />
-------------------------------------<br />
His findings were as revolutionary as Gödel’s own. Since that time, mathematicians have built up two different mathematical worlds, one in which the continuum hypothesis applies and one in which it does not, and modern mathematical proofs must insert a statement declaring whether or not the result depends on the continuum hypothesis.<br />
-------------------------------------<br />
<br />
When was the last time you had to put into the premise of a theorem CH or NOT-CH?<br />
I did once <a href="http://arxiv.org/abs/1201.1207">here</a> in an expository work about a problem in combinatorics that was ind of set theory since it was equivalent to CH. Before you get too excited it was a problem in infinite combinatorics having to do with coloring the reals.<br />
<br />
I suspect that at least 99% of my readers have never had to insert a note in a paper about if they were assuming CH or NOT-CH. If you have I'd love to hear about it in the comments. And I suspect<br />
you are a set theorist.<br />
<br />
Paul Cohen's work was very important--- here we have an open problem in math that will always be open (thats one interpretation). And there will sometimes be other problems that are ind of ZFC or equiv to CH or something like that. But it does not affect the typical mathematician working on a typical problem.<br />
<br />
I have a sense that its bad to exaggerate like this. One reason would be that if the reader finds out<br />
the truth he or she will be disillusioned. But somehow, that doesn't seem to apply here. So I leave it to the reader to comment: Is it bad to exaggerate Paul Cohen's (or anyone's) accomplishments? And if so,<br />
then why?<br />
<br />
<br />http://blog.computationalcomplexity.org/2016/10/exaggeration-is-one-thing-but-this-is.htmlnoreply@blogger.com (GASARCH)4