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NIPS
2007
15 years 7 months ago
Optimistic Linear Programming gives Logarithmic Regret for Irreducible MDPs
We present an algorithm called Optimistic Linear Programming (OLP) for learning to optimize average reward in an irreducible but otherwise unknown Markov decision process (MDP). O...
Ambuj Tewari, Peter L. Bartlett
ERSA
2006
111views Hardware» more  ERSA 2006»
15 years 7 months ago
Promises and Pitfalls of Reconfigurable Supercomputing
Reconfigurable supercomputing (RSC) combines programmable logic chips with high performance microprocessors, all communicating over a high bandwidth, low latency interconnection n...
Maya Gokhale, Christopher Rickett, Justin L. Tripp...
NIPS
2001
15 years 7 months ago
Variance Reduction Techniques for Gradient Estimates in Reinforcement Learning
Policy gradient methods for reinforcement learning avoid some of the undesirable properties of the value function approaches, such as policy degradation (Baxter and Bartlett, 2001...
Evan Greensmith, Peter L. Bartlett, Jonathan Baxte...
BIOCOMP
2009
15 years 7 months ago
Improving Remote Homology Detection Using Sequence Properties and Position Specific Scoring Matrices
Current biological sequence comparison tools frequently fail to recognize matches between homologs when sequence similarity is below the twilight zone of less than 25% sequence id...
Gina Cooper, Michael L. Raymer
GECCO
2008
Springer
168views Optimization» more  GECCO 2008»
15 years 7 months ago
Parameterizing pair approximations for takeover dynamics
Pair approximations have often been used to predict equilibrium conditions in spatially-explicit epidemiological and ecological systems. In this work, we investigate whether this ...
Joshua L. Payne, Margaret J. Eppstein