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» Localizing Search in Reinforcement Learning
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FOCS
1999
IEEE
14 years 2 months ago
Learning Mixtures of Gaussians
Mixtures of Gaussians are among the most fundamental and widely used statistical models. Current techniques for learning such mixtures from data are local search heuristics with w...
Sanjoy Dasgupta
COLING
2002
13 years 9 months ago
Fine Grained Classification of Named Entities
While Named Entity extraction is useful in many natural language applications, the coarse categories that most NE extractors work with prove insufficient for complex applications ...
Michael Fleischman, Eduard H. Hovy
ICML
1999
IEEE
14 years 10 months ago
Distributed Value Functions
Many interesting problems, such as power grids, network switches, and tra c ow, that are candidates for solving with reinforcement learningRL, alsohave properties that make distri...
Jeff G. Schneider, Weng-Keen Wong, Andrew W. Moore...
GECCO
2009
Springer
258views Optimization» more  GECCO 2009»
14 years 2 months ago
Evolutionary learning of local descriptor operators for object recognition
Nowadays, object recognition is widely studied under the paradigm of matching local features. This work describes a genetic programming methodology that synthesizes mathematical e...
Cynthia B. Pérez, Gustavo Olague
TSMC
1998
78views more  TSMC 1998»
13 years 9 months ago
Automata learning and intelligent tertiary searching for stochastic point location
—Consider the problem of a robot (learning mechanism or algorithm) attempting to locate a point on a line. The mechanism interacts with a random environment which essentially inf...
B. John Oommen, Govindachari Raghunath