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SIAMSC
2010
215views more  SIAMSC 2010»
15 years 26 days ago
A Fast Algorithm for Sparse Reconstruction Based on Shrinkage, Subspace Optimization, and Continuation
We propose a fast algorithm for solving the ℓ1-regularized minimization problem minx∈Rn µ x 1 + Ax − b 2 2 for recovering sparse solutions to an undetermined system of linea...
Zaiwen Wen, Wotao Yin, Donald Goldfarb, Yin Zhang
CORR
2010
Springer
105views Education» more  CORR 2010»
15 years 1 months ago
Optimism in Reinforcement Learning Based on Kullback-Leibler Divergence
We consider model-based reinforcement learning in finite Markov Decision Processes (MDPs), focussing on so-called optimistic strategies. Optimism is usually implemented by carryin...
Sarah Filippi, Olivier Cappé, Aurelien Gari...
FLAIRS
2003
15 years 3 months ago
Identifying Inhabitants of an Intelligent Environment Using a Graph-Based Data Mining System
The goal of the MavHome smart home project is to build an intelligent home environment that is aware of its inhabitants and their activities. Such a home is designed to provide ma...
Ritesh Mehta, Diane J. Cook, Lawrence B. Holder
UAI
2001
15 years 3 months ago
The Optimal Reward Baseline for Gradient-Based Reinforcement Learning
There exist a number of reinforcement learning algorithms which learn by climbing the gradient of expected reward. Their long-run convergence has been proved, even in partially ob...
Lex Weaver, Nigel Tao
JMLR
2012
13 years 4 months ago
Bayesian Comparison of Machine Learning Algorithms on Single and Multiple Datasets
We propose a new method for comparing learning algorithms on multiple tasks which is based on a novel non-parametric test that we call the Poisson binomial test. The key aspect of...
Alexandre Lacoste, François Laviolette, Mar...