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TSP
2010
13 years 3 months ago
Double sparsity: learning sparse dictionaries for sparse signal approximation
Abstract--An efficient and flexible dictionary structure is proposed for sparse and redundant signal representation. The proposed sparse dictionary is based on a sparsity model of ...
Ron Rubinstein, Michael Zibulevsky, Michael Elad
ML
2000
ACM
157views Machine Learning» more  ML 2000»
13 years 8 months ago
A Multistrategy Approach to Classifier Learning from Time Series
We present an approach to inductive concept learning using multiple models for time series. Our objective is to improve the efficiency and accuracy of concept learning by decomposi...
William H. Hsu, Sylvian R. Ray, David C. Wilkins
ECML
2005
Springer
14 years 2 months ago
Model-Based Online Learning of POMDPs
Abstract. Learning to act in an unknown partially observable domain is a difficult variant of the reinforcement learning paradigm. Research in the area has focused on model-free m...
Guy Shani, Ronen I. Brafman, Solomon Eyal Shimony
NIPS
2008
13 years 10 months ago
Nonparametric Bayesian Learning of Switching Linear Dynamical Systems
Many nonlinear dynamical phenomena can be effectively modeled by a system that switches among a set of conditionally linear dynamical modes. We consider two such models: the switc...
Emily B. Fox, Erik B. Sudderth, Michael I. Jordan,...
COLT
2006
Springer
14 years 22 days ago
Active Sampling for Multiple Output Identification
We study functions with multiple output values, and use active sampling to identify an example for each of the possible output values. Our results for this setting include: (1) Eff...
Shai Fine, Yishay Mansour