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ATAL
2007
Springer
15 years 3 months ago
Model-based function approximation in reinforcement learning
Reinforcement learning promises a generic method for adapting agents to arbitrary tasks in arbitrary stochastic environments, but applying it to new real-world problems remains di...
Nicholas K. Jong, Peter Stone
PODS
1995
ACM
139views Database» more  PODS 1995»
15 years 1 months ago
Normalizing Incomplete Databases
Databases are often incomplete because of the presence of disjunctive information, due to con icts, partial knowledge and other reasons. Queries against such databases often ask q...
Leonid Libkin
DIS
2010
Springer
14 years 8 months ago
Discovery of Conservation Laws via Matrix Search
Abstract. One of the main goals of Discovery Science is the development and analysis of methods for automatic knowledge discovery in the natural sciences. A central area of natural...
Oliver Schulte, Mark S. Drew
SIAMIS
2011
14 years 4 months ago
NESTA: A Fast and Accurate First-Order Method for Sparse Recovery
Abstract. Accurate signal recovery or image reconstruction from indirect and possibly undersampled data is a topic of considerable interest; for example, the literature in the rece...
Stephen Becker, Jérôme Bobin, Emmanue...
JMLR
2011
148views more  JMLR 2011»
14 years 4 months ago
Multitask Sparsity via Maximum Entropy Discrimination
A multitask learning framework is developed for discriminative classification and regression where multiple large-margin linear classifiers are estimated for different predictio...
Tony Jebara