December 2011
9 posts
How to conduct your own annual review →
Dec 30th
Large deviations for the local fluctuations of random walks and new insights into the “randomness” of Pi http://arxiv.org/abs/1004.3713v2
Dec 11th
Active Learning Halfspaces under Margin Assumptions http://arxiv.org/abs/1112.1556v1
Dec 11th
Predictors for time series with energy decay on higher frequencies http://arxiv.org/abs/1112.1478v1
Dec 10th
Information-Theoretically Optimal Compressed Sensing via Spatial Coupling and Approximate Message Passing http://arxiv.org/abs/1112.0708v1
Dec 7th
On the question of effective sample size in network modeling http://arxiv.org/abs/1112.0840v1
Dec 7th
2 tags
Dimension adaptability of Gaussian process models...
http://arxiv.org/abs/1112.0716v1
Dec 6th
2 tags
Multi-stage Convex Relaxation for Feature Selection http://arxiv.org/abs/1106.0565v2
Dec 6th
2 tags
Machine learning with operational costs
http://arxiv.org/abs/1112.0698v1
Dec 6th
October 2011
0 posts
Model Selection in Reinforcement Learning
Csaba Szepesvári and I have a new paper about the model selection problem in reinforcement learning. This paper, which is published by the Machine Learning Journal, considers the batch (offline, non-interactive) reinforcement learning setting when the goal is to find an action-value function with the smallest Bellman error among a countable set of candidate functions. We prove an oracle-like...
Oct 1st
Theoretical Computer Science Cheat sheet →
Includes Order notation, Series, Combinatorics, Recurrences, Probability, Trigonometric, Calculus, Series expansion, and many other things.
Oct 3rd
July 2010
2 posts
The Three Golden Rules for Successful Scientific... →
by Dijkstra.
Jul 29th
GRASP Lecture Series →
Jul 10th
June 2010
3 posts
1 tag
Approximate Dynamic Programming via Iterated... →
By Wang and Boyd.
Jun 11th
A Course on Convex Optimization →
By Stephen Boyd.
Jun 11th
Workshop on Simulation Optimization →
Jun 9th
April 2010
1 post
1 tag
Stability Bounds for Stationary phi and... →
JMLR 2010 paper by Mehryar Mohri and Afshin Rostamizadeh.
Apr 22nd
March 2010
1 post
1 tag
Stochastic Optimization (James Spall) →
Talks about SPSA, FDSA, and GA.
Mar 26th
January 2010
1 post
Sam Roweis died
So sad that such an energetic and nice person perishes this way.
Jan 15th
December 2009
1 post
Ray Solomonoff (1926 - 2009)
Ray Solomonoff passed away last week.
Dec 15th
October 2009
5 posts
Processing →
“Processing is an open source programming language and environment for people who want to program images, animation, and interactions.”
Oct 23rd
1 tag
Model Selection Homepage →
Oct 23rd
Ph.D. Candidate!
I am a Ph.D. candidate since 16:30 today! Hurray!
Oct 8th
“Focusing on important questions puts us in the awkward position of being...”
– The importance of stupidity in scientific research by Martin A. Schwartz.
Oct 7th
How to Publish in Top Journals →
by Kwan Choi.
Oct 1st
September 2009
3 posts
1 tag
Unlabeled data: Now it helps, now it doesn’t →
by Aarti Singh, Robert Nowak, and Xiaojin Zhu.
Sep 30th
1 tag
Sep 29th
1 tag
Relations between Probability Distributions
Distributions diagrams (also this article by Leemis and McQuestion) Conjugate Priors (also Compendium of Conjugate Priors by Daniel Fink) (credit: I found these links here.)
Sep 12th
August 2009
6 posts
Sobolev Embedding Theorems, Besov Spaces, etc.
First we need the definition of Hölder and Sobolev spaces (Wikipedia). The idea of Hölder spaces is that the k-th derivative of the functions are alpha-Lipschitz. The idea of Sobolev spaces is that the k-th derivate of the functions are in Lp space. Then we have different Sobolev inequalities. These inequalities basically say which Sobolev space can be embedded in another one. Of course, if two...
Aug 31st
1 tag
Generalized Representer Theorem
Scholkopf, Herbrich, Smola, “Generalized Representer Theorem”. The theorem is quite general: for an arbitrary loss function L(.) that depends on data x_1,…,x_m, and regularizer in the form of g(||f||) with g(.) as strictly monotonic increasing, we have the usual expansion in the form of f(.) = \sum_{i=1}^m a_i k(.,x_i) . Also the Remark 6, biased regularization, is quite...
Aug 13th
2 tags
Homepage of K. Avrachenkov →
Perturbation theory for Markov Chains
Aug 8th
1 tag
Fixed point theorems in infinite-dimensional... →
from Wikipedia. Take a look at Schauder fixed-point theorem too.
Aug 3rd
1 tag
Some presentations from Yousef Saad on... →
Interesting!
Aug 3rd
1 tag
Cubic regularization of Newton method and its... →
By Nesterov and Polyak.
Aug 3rd
July 2009
1 post
Research productivity: some paths less travelled (Brian Martin) http://www.uow.edu.au/arts/sts/bmartin/pubs/09aur.html
Jul 24th
May 2009
2 posts
Advices to a Young Mathematician →
May 31st
1 tag
Inequalities for the L1 deviations of the... →
by Weissman, Ordentlich, Seroussi, Verdu, Weinberger.
May 17th
March 2009
5 posts
2 tags
On Fast Rates in Classification
I am wondering what types of regularities are natural to be used in classification problems. In regression setting, different notion of smoothness appears naturally in the bound. I was wondering if I could find similar results for classification. The field’s landscape is not clear to me yet. People use margin noise conditions that may give them fast rates (faster than n^{-1/2}). If their...
Mar 24th
2 tags
Rapid Mixing in Markov Chains →
By R. Kannan.
Mar 18th
2 tags
Reliable Reason: Induction and Statistical... →
A book by Gilbert Harman and Sanjeev Kulkarni on philosophy of science - an STL approach.
Mar 12th
1 tag
On Pattern Theory (David Mumford)
David Mumford, “Empirical Statistics and Stochastic Models for Visual Signals”. David Mumford, “Pattern Theory: the Mathematics of Perception” (presentation slides)
Mar 8th
1 tag
How to Compare Different Loss Functions and Their... →
by Ingo Steinwart.
Mar 3rd
February 2009
5 posts
2 tags
Evolutionary Epistemology (EET and EEM) →
Feb 15th
1 tag
Conditional Density Estimation
Chen, Linton and Robinson, “The Estimation of Conditional Densities”. (some interesting results regarding the mixing properties for Markov models) Hansen, “Nonparametric Conditional Density Estimation,” 2004. (Two-stage method for conditional density estimation: estimate the mean, and then estimate the deviation from the mean) Yoon, “Bayesian Conditional Density...
Feb 13th
1 tag
A few papers by Terrence J. Sejnowski
L. Finelli and T. Sejnowski, “What is Consolidated During Sleep-Dependent Motor Skill Learning?,” 2005. T. Flash and T. Sejnowski, “Computational Approaches to Motor Control,” 2001. D. Garlick and T. Sejnowski, “There is more to Fluid Intelligence than Working Memory Capacity and Executive Function,” 2006. T. Sejnowski, “Sleep and Memory,” 1995.
Feb 11th
1 tag
Yuhong Yang →
Feb 6th
2 tags
A Few Papers on ADP and etc from Bertsekas et al.
H. Yu and D. Bertsekas, Basis Function Adaptation Methods for Cost Approximation in MDP, 2009. H. Yu and D. Bertsekas, New Error Bounds for Approximations from Projected Linear Equations, 2008. H. Yu and D. Bertsekas, A Least Squares Q-Learning Algorithm for Optimal Stopping Problems, 2006. D. Bertsekas, Dynamic Programming and Suboptimal Control: A Survey from ADP to MPC, 2005. D. Bertsekas,...
Feb 3rd
January 2009
5 posts
Mathematical Issues in Dynamic Programming →
by Dimitri Bertsekas and Steven Shreve. Talks about the measurability problems one may face when he wants to deal with uncountable state spaces.
Jan 28th
3 tags
Stochastic Approximation: A Dynamical Systems... →
A book by Vivek S. Borkar. Thanks to Francisco Melo for the pointer.
Jan 24th
1 tag
Active Learning Literature Survey →
by Burr Settles.
Jan 23rd