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Posts

January 25, 2015

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Today's first insight, is a follow up to several Sunday Morning Insights. The first cast genome sequencing as how a formerly NP-Hard problem (Sunday Morning Insight: Escaping Feynman's NP-Hard "Map of a Cat": Genomic Sequencing Edition), the second one was on how Advanced Matrix Factorization can now help speed up this technology ( Improving Pacific Biosciences' Single Molecule Real Time Sequencing Technology through Advanced Matrix Factorization ? ). Then, we conjectured, based on our previous […]
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I decided to create handouts for warm ups for one of my second semester classes. I wanted to formalize some of what I already do to help strengthen their number sense. I plan on doing counting circles which my students really seem to dislike(!). Nevertheless, I think there is great value in doing counting circles, both in terms of the skills and the culture it helps develop in the classroom. We will also be doing more Estimation 180, Visual Patterns, Would you Rather along with balance benders, […]
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Busy week, teaching begins in Newcastle, this semester I shall be teaching MAS3111: Partial Differential Equations with Applications. I will also be giving a seminar down in Durham on Friday, as part of their numerical analysis series: https://www.dur.ac.uk/mathematical.sciences/events/seminars/?series=10
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This arrived a couple weeks ago from Nassim Taleb. Regardless of where your view falls on the black swan spectrum, I hope you'll like the graphic. One hallmark of a good graphic is that it repays careful study, as with a good map (which is a good graphic). Nassim's Genealogy certainly passes that test. I found myself thinking about its contents and assertions for a long time. (You can blow it up in your browser by clicking on it. That should do the trick, but if it's still not […]
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Every year, the Department of Statistics at the University of Auckland offers summer scholarships to a number of students so they can work with staff on real-world projects. Rahul Singhal, right, is working on a project called Developing Bias Weights for the New Zealand Longitudinal Census with Professor Alan Lee. Rahul explains: “The project attempts […]
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References: Griffiths, David J. (2007), Introduction to Electrodynamics, 3rd Edition; Pearson Education – Chapter 11, Post 11. In analyzing radiation from an arbitrary configuration of charge, we made the assumption that the maximum dimension of the source is much smaller than the observation distance, so that we can retain only first order terms in , […]
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References: Griffiths, David J. (2007), Introduction to Electrodynamics, 3rd Edition; Pearson Education – Chapter 11, Post 10. If a charge falls under the influence of gravity, it accelerates and therefore radiates. This means that not all of the potential energy lost as the charge falls is converted to kinetic energy, so a charged object falls […]
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References: Griffiths, David J. (2007), Introduction to Electrodynamics, 3rd Edition; Pearson Education – Chapter 11, Post 9. Here’s a generalization of the rotating dipole problem we did earlier. This time we have a circular ring with radius with a linear charge distribution, at , of where is the azimuthal angle. The disk is set spinning […]
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References: Griffiths, David J. (2007), Introduction to Electrodynamics, 3rd Edition; Pearson Education – Chapter 11, Post 8. Having examined electromagnetic radiation from an oscillating electric dipole, we can now look at radiation from an arbitrary source of moving charges. The derivation of the results is rather long and Griffiths treats it in detail in his […]
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We’ll ask an expert, or even a student, to “tell me what you know” about some topic. But now I’m thinking it makes more sense to ask people to tell us what they don’t know. Why? Consider your understanding of a particular topic to be divided into three parts: 1. What you know. 2. What […] The post Tell me what you don’t know appeared first on Statistical Modeling, Causal Inference, and Social Science.
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Here Gauss derives an expression for the curvature of a surface. This was a key step in the demonstration, which Gauss described as “remarkable”, that curvature is an intrinsic property of the surface and not of how it’s embedded in … Continue reading →
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The third and final day, and the talks were again excellent!  Catia Dias started off by showing off the results of her very thorough Ph.D. thesis.  She discovered and proved many properties of game values and the lattices of their followers, which I think she generated using the generalized Conway construction.  Her talk was extremely thorough as she took on and solved many conjectures.  (I later learned that Richard Nowakowski had proposed three of these conjectures.)  […]
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Hop the Q-TRAIN: that is, the Quantitative Training Program, a postdoctoral research program supervised by Jennifer Hill, Marc Scott, and myself, and funded by the Institute for Education Sciences. As many of you are aware, education research is both important and challenging. And, on the technical level, we’re working on problems in Bayesian inference, multilevel […] The post Postdoc opportunity here, with us (Jennifer Hill, Marc Scott, and me)! On quantitative education […]
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The accepted paper list!http://www.optimalmatching.com/MATCHUP2015/accepted-abstracts.html

January 24, 2015

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Overview In previous posts I’ve shown how the jvmr CRAN R package can be used to call Scala sbt projects from R and inline Scala Breeze code in R. In this post I will show how to call to R from a Scala sbt project. This requires that R and the jvmr CRAN R package […]
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The international Biomedical and Astronomical Signal Processing (BASP) Frontiers workshop starts tomorrow. The proceedings are here.  The ski report lists Avalanche Level is rated "Considerable Danger" so it might be wise to stay warm and talk real science. Here is the program:Sunday January 25, 201513.00 - 14.30    Aperitif and standing lunch13.30 - 14.00    Lunch14.00 - 15.45    Free time15.45 - 16.00    […]
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Time passes quickly, my friends. It seems like only yesterday that Aunt Pythia was answering really long questions, and today her questions seem to be extra short. Last week it was cold outside – freezing! – but this week it is warm and snowy (but not for long!). Last week she was knitting a cowl, this […]
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No summary available for this post.
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Someone who wishes to remain anonymous writes in: Last week, I was looking forward to a blog post titled “Why continue to teach and use hypothesis testing?” I presume that this scheduled post merely became preempted by more timely posts. But I am still interested in reading the exchange that will follow. My feeling is […] The post “What then should we teach about hypothesis testing?” appeared first on Statistical Modeling, Causal Inference, and Social Science.
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Note the use of conservation of energy. Joules famous experiments on the conversion of mechanical motion to heat were done when Kelvin was around 20 years old. When we consider the moon as causing the tides, and the change from … Continue reading →
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Via Felix Salmon, here’s a chart from Credit Suisse that’s been making the headlines recently, in the Oxfam report on global wealth.  The chart shows where in the world people live for each of the ‘wealth’ deciles, and I’ve circled the most interesting piece. About 10% of the least wealthy people in the world live in […]
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Moral decision making is one of the major torrents in human behavior. It often overrides other ways of making judgments, it generates conflicting sets of cultural values and is reinforced by them. Such conflicts might even occur in the head of some unfortunate individual, which makes the process really creative. On the other hand ethical […]

January 23, 2015

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How could I have missed this one from the papers currently in review for ICLR 2015 ? In fact, I did not miss it, I read it and then ... other things took over. So without further ado, here is the starting point of the study: ...Consider, however, the results shown in Figure 1, where we trained networks of increasing size on the MNIST and CIFAR-10 datasets. Training was done using stochastic gradient descent with momentum and diminishing step sizes, on the training error and without any explicit […]
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Videos are fourth order tensors that have much information. The following paper shows how much of it through Low rank Tensor reconstruction. Woohoo ! New Ranks for Even-Order Tensors and Their Applications in Low-Rank Tensor Optimization by Bo Jiang, Shiqian Ma, Shuzhong ZhangIn this paper, we propose three new tensor decompositions for even-order tensors corresponding respectively to the rank-one decompositions of some unfolded matrices. Consequently such new decompositions lead to three new […]
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In my HBR article about A/B testing (link), I described one of the key managerial problems related to A/B testing--the surplus of “positive” results that don’t quite seem to add up. In particular, I mentioned this issue: When managers are reading hour-by-hour results, they will sometimes find large gaps between Groups A and B, and demand prompt reaction. Almost all such fluctuations result from temporary imbalance between the two groups, which gets corrected as new samples arrive. Over […]
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매번 집 앞 마트에서 800원 주고 환타 포도 캔을 사서 마시는데.. 생각해 보니 마트 호구짓을 하는 것 같아서.. 어차피 매일 마시는거 1달치를 대량으로 구매하면 얼마나 득을 볼 수 있나 찾아봤다. 옥션에서 찾아 봤더니 30개를 13,000원에 팔고 있었다. 헐.. 개당 433원..! … Continue reading →Related Posts ?다시 찾은 낙산공원 – 광각렌즈 사망마을 뒷산 – 낙산공원 겨울 […]
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So . . . the scheduled debate on using margin of error with non-probability panels never happened. We got it started but there was some problem with the webinar software and nobody put the participants could hear anything. The 5 minutes of conversation we did have was pretty good, though. I was impressed. The webinar […] The post What’s the point of the margin of error? appeared first on Statistical Modeling, Causal Inference, and Social Science.
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Reading this David Leonhardt piece (Letter From the Editor: Marriage, and When Liberals Are Wrong) is like watching the Three Stooges working in a hardware store -- Here's where he steps on the rake. Here's where he drops the anvil on his foot. Here's where he walks into the buzz saw -- but with the crucial difference that the Stooges at least had some glimmer of awareness after the injury (even Curly would get up off of the stove when his pants started to smoke). Leonhardt doesn't […]
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The lasso introduced as an improvement to regression, ridge regression and subset selection. Consider the usual regression situation: we have data , i=1, 2,…, N, where and are the regressors and response for the ith observation. The ordinary least squares … Continue reading →