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» Optimal Sequential Exploration: A Binary Learning Model
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CVPR
2010
IEEE
16 years 14 days ago
Exploring Features in a Bayesian Framework for Material Recognition
We are interested in identifying the material category, e.g. glass, metal, fabric, plastic or wood, from a single image of a surface. Unlike other visual recognition tasks in comp...
Ce Liu, Lavanya Sharan, Edward Adelson, Ruth Rosen...
COLT
2010
Springer
15 years 2 months ago
An Asymptotically Optimal Bandit Algorithm for Bounded Support Models
Multiarmed bandit problem is a typical example of a dilemma between exploration and exploitation in reinforcement learning. This problem is expressed as a model of a gambler playi...
Junya Honda, Akimichi Takemura
ICMLA
2009
15 years 1 months ago
Structured Prediction Models for Chord Transcription of Music Audio
Chord sequences are a compact and useful description of music, representing each beat or measure in terms of a likely distribution over individual notes without specifying the not...
Adrian Weller, Daniel P. W. Ellis, Tony Jebara
ICANNGA
2009
Springer
212views Algorithms» more  ICANNGA 2009»
15 years 10 months ago
Evolutionary Regression Modeling with Active Learning: An Application to Rainfall Runoff Modeling
Many complex, real world phenomena are difficult to study directly using controlled experiments. Instead, the use of computer simulations has become commonplace as a feasible alte...
Ivo Couckuyt, Dirk Gorissen, Hamed Rouhani, Eric L...
IJCAI
2001
15 years 5 months ago
R-MAX - A General Polynomial Time Algorithm for Near-Optimal Reinforcement Learning
R-max is a very simple model-based reinforcement learning algorithm which can attain near-optimal average reward in polynomial time. In R-max, the agent always maintains a complet...
Ronen I. Brafman, Moshe Tennenholtz