Selected topics on, but not restricted to, machine learning, optimization and game theory <br> by <a href="http://cs.princeton.edu/~ehazan">Elad Hazan</a> and group @ Princeton University
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Minimizing Regret | minimizingregret.com Reviews
https://minimizingregret.com
Selected topics on, but not restricted to, machine learning, optimization and game theory <br> by <a href="http://cs.princeton.edu/~ehazan">Elad Hazan</a> and group @ Princeton University
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Minimizing Regret: Duality for undergrads
http://www.minimizingregret.com/2011/01/duality-for-undergrads.html
Selected topics on, but not restricted to, machine learning, optimization and game theory. Thursday, February 3, 2011. Of linear programming and its extensions is a fundamental pillar of optimization. It lies at the heart of an elegant theory which allows us not only to reason about the structure of continuous optimization problems, but also design combinatorial optimization and approximation algorithms. John von Neumann said that In mathematics you don't understand things. You just get used to them.
Minimizing Regret: February 2011
http://www.minimizingregret.com/2011_02_01_archive.html
Selected topics on, but not restricted to, machine learning, optimization and game theory. Monday, February 21, 2011. Worst-case vs. average-case learning. Classical statistical learning theory deals with finding a consistent hypothesis given sufficiently many examples. Such a hypothesis may be a rule for classifying emails into spam/not-spam, and examples are classified emails. Here comes online learning theory: in online learning we do not make any assumptions about the data, but rather sequentially mo...
Minimizing Regret: Worst-case vs. average-case learning
http://www.minimizingregret.com/2011/02/worst-case-vs-average-case-learning.html
Selected topics on, but not restricted to, machine learning, optimization and game theory. Monday, February 21, 2011. Worst-case vs. average-case learning. Classical statistical learning theory deals with finding a consistent hypothesis given sufficiently many examples. Such a hypothesis may be a rule for classifying emails into spam/not-spam, and examples are classified emails. Here comes online learning theory: in online learning we do not make any assumptions about the data, but rather sequentially mo...
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Links | OptiML
http://optiml.cs.princeton.edu/index.php/links
Optimization and Machine Learning. Latest News from OptiML. Check out our new blog: minimizingregret.com. Containing a post on our Linear Time Second Order Stochastic Algorithm. About a year ago. Via Twitter Web Client. Our new paper LiSSA on Linear Time Stochastic Second Order Methods is online : arxiv.org/abs/1602.03943. About a year ago. Via Twitter Web Client. Proudly powered by WordPress.
Uncategorized | OptiML
http://optiml.cs.princeton.edu/index.php/category/uncategorized
Optimization and Machine Learning. March 2, 2016. Welcome to WordPress. This is your first post. Edit or delete it, then start writing! Latest News from OptiML. Check out our new blog: minimizingregret.com. Containing a post on our Linear Time Second Order Stochastic Algorithm. About a year ago. Via Twitter Web Client. Our new paper LiSSA on Linear Time Stochastic Second Order Methods is online : arxiv.org/abs/1602.03943. About a year ago. Via Twitter Web Client. Proudly powered by WordPress.
Spielman-Teng-B: Spectral Sparsification of Graphs (Part I) | Fly Fly Fly the Butterfly
https://zeyuan.wordpress.com/2012/06/02/spielman-teng-b-1
Fly Fly Fly the Butterfly. Constant Factor Approximation of Vertex-Cuts in Planar Graphs. Spielman-Teng-B: Spectral Sparsification of Graphs (Part II) →. Spielman-Teng-B: Spectral Sparsification of Graphs (Part I). June 2, 2012. Spielman-Teng’s 2004 paper [ST04]. On almost-linear Laplacian linear solver has been divided and re-written into three very technically involved papers [ST08a]. The goal of [ST08b] is to construct a re-weighted subgraph of. Edges that is a. So that the new graph has. Edges Becaus...
Fly Fly Fly the Butterfly | Zeyuan Allen-Zhu | Page 2
https://zeyuan.wordpress.com/page/2
Fly Fly Fly the Butterfly. Newer posts →. Spielman-Teng-B: Spectral Sparsification of Graphs (Part II). June 3, 2012. Spielman-Teng’s 2004 paper [ST04]. On almost-linear Laplacian linear solver has been divided and re-written into three very technically involved papers [ST08a]. I am planning to write memos for all of them, while this post is the Part II for the second paper [ST08b: Spectral Sparsification of Graphs. Recap and Today’s Goal. Spielman-Teng-B: Spectral Sparsification of Graphs (Part I).
May | 2011 | Fly Fly Fly the Butterfly
https://zeyuan.wordpress.com/2011/05
Fly Fly Fly the Butterfly. Monthly Archives: May 2011. Learning Algorithms for DT, DNF, AC0 and r-juntas. May 25, 2011. This is a section of my reading notes to Prof. Ryan O’Donnell’s Analysis of Boolean Functions , I’ve summarized the learning algorithms in this post, which also functions as a personal reference. Class Random Examples Membership Queries poly-size DTs Theorem 5 Theorem … Continue reading →. Fly Fly Fly the Butterfly. Blog at WordPress.com. Fly Fly Fly the Butterfly.
Constant Factor Approximation of Vertex-Cuts in Planar Graphs | Fly Fly Fly the Butterfly
https://zeyuan.wordpress.com/2012/05/13/constant-factor-approximation-of-vertex-cuts-in-planar-graphs
Fly Fly Fly the Butterfly. Learning Algorithms for DT, DNF, AC0 and r-juntas. Spielman-Teng-B: Spectral Sparsification of Graphs (Part I) →. Constant Factor Approximation of Vertex-Cuts in Planar Graphs. May 13, 2012. For a semester, and learned many interesting stuff. This time I’m going to blog Amir-Krauthgamer-Rao’s STOC 2003. Result on planar graph vertex-cut problem. In planar graph, we can define. Quotient cost is (where. And in terms of constant approximations, this constant. And then find the edg...
Almost Perfect Bisection 2 | Fly Fly Fly the Butterfly
https://zeyuan.wordpress.com/2011/01/21/almost-perfect-bisection-2
Fly Fly Fly the Butterfly. Course Study Group with Xiaorui Sun. Infinity in Game Theory →. Almost Perfect Bisection 2. January 21, 2011. This time I’m going to introduce A polylogarithmic approximation of the minimum bisection. By Uriel Feige and Robert Krauthgamer. I will transfer my language to minimum bisection rather than maximum bisection, as they two transform to each other for obvious reason. This paper proved that if an. Fraction of) edges. This is later improved to. Find the min cut. This paper ...
June | 2012 | Fly Fly Fly the Butterfly
https://zeyuan.wordpress.com/2012/06
Fly Fly Fly the Butterfly. Monthly Archives: June 2012. Spielman-Teng-A: A Local Clustering Algorithm for Massive Graphs and its Application to Nearly-Linear Time Graph Partitioning. June 3, 2012. Spielman-Teng’s 2004 paper [ST04] on almost-linear Laplacian linear solver has been divided and re-written into three very technically involved ones [ST08a], [ST08b] and [ST08c]. I am planning to write memos for all of them, while this post is the Part … Continue reading →. June 3, 2012. June 2, 2012.
Spielman-Teng-A: A Local Clustering Algorithm for Massive Graphs and its Application to Nearly-Linear Time Graph Partitioning | Fly Fly Fly the Butterfly
https://zeyuan.wordpress.com/2012/06/03/spielman-teng-a
Fly Fly Fly the Butterfly. Spielman-Teng-B: Spectral Sparsification of Graphs (Part II). The Complexity Zoo and Reductions in Optimization →. Spielman-Teng-A: A Local Clustering Algorithm for Massive Graphs and its Application to Nearly-Linear Time Graph Partitioning. June 3, 2012. Spielman-Teng’s 2004 paper [ST04]. On almost-linear Laplacian linear solver has been divided and re-written into three very technically involved ones [ST08a]. That satisfies for any cut. Is also of further use in [ST08b] to co...
Spielman-Teng-B: Spectral Sparsification of Graphs (Part II) | Fly Fly Fly the Butterfly
https://zeyuan.wordpress.com/2012/06/03/spielman-teng-b-2
Fly Fly Fly the Butterfly. Spielman-Teng-B: Spectral Sparsification of Graphs (Part I). Spielman-Teng-A: A Local Clustering Algorithm for Massive Graphs and its Application to Nearly-Linear Time Graph Partitioning →. Spielman-Teng-B: Spectral Sparsification of Graphs (Part II). June 3, 2012. Spielman-Teng’s 2004 paper [ST04]. On almost-linear Laplacian linear solver has been divided and re-written into three very technically involved papers [ST08a]. Recap and Today’s Goal. There is a procedure ApproxCut.
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less IS more
So to be better than I am, better than I was, and better than I will be is to become something more than JUST me. How do I do that? I have to minimize me to make room for what is to be.come join me and we shall see what’s next!
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Discover Parallels Virtuozzo Containers. This domain minimizingmistakes.net. This page has been automatically generated by Parallels Operations Automation. Australian Style Pty. Ltd.
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Minimizing My Closet | Rebecca's Ramblings About Various Clothing Simplification Projects
Rebecca's Ramblings About Various Clothing Simplification Projects. Evaluation of my First Project 333 Cycle. June 28, 2011. My first project 333 cycle is winding down since there are only a few days left in June. I found that I wore about half of the things I planned to wear, but also added in some items I wasn’t expecting to wear. I think because of this, for cycle 2, I will go the more spontaneous route. So for July-August-September, I will make things a part of my 33 as I wear them the first time.
Minimizing Regret
Selected topics on, but not restricted to, machine learning, optimization and game theory. And group @ Princeton University. Thursday, March 1, 2018. Unsupervised learning III: worst-case compression-based metrics that generalize. 1 I owe a followup to the stubborn few readers of the blog who have made it thus far. 2 The algorithms well discuss are mathematically correct, and even if completely useless in practice, can serve as amusement to us, fans of regret minimization in convex games. It is thus part...
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Working to reduce violence in the community. Please join us to celebrate our annual Day of Nonviolence at an awards lunch to present the Bob Tunks Peace Award to deserving individuals and organizations. 1995 Men Evolving Nonviolently. 1998 Robin Bowen (California Parenting Institute). 2001 Dyan Foster (Routes for Youth, Teen Court). 2002 Lynn Sherrard-Stuhr (El Nido Teen Center) and Lynn Garric (Sonoma County Office of Education). 2004 Sonoma County Juvenile Probation Camp. Gig Hitao, President. Please e...
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Burak Kuyucaklı’nın kodlama. Oluşan, hep - yine denemelerini. Içerir web sayfasıdır. İstanbulda doğdu. Marmara Üniversitesi Güzel Sanatlar Fakültesi resim bölümünündeki eğitiminin ardından yüksek lisans eğitimine Yıldız Teknik Üniversitesi Sanat ve Tasarım bölümünde devam etti. Tezini tamamlamadan bu bölümden ayrıldı. Lisans sürecinden itibaren, resim eğitiminin yanında web. Alanlarına da ilgi duydu. Katıldığı sergilerde daha çok kendi yazdığı basit kodlarla çalışan yerleştirmeler.
