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» Learning for stochastic dynamic programming
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HICSS
2009
IEEE
108views Biometrics» more  HICSS 2009»
15 years 9 months ago
Approximate Dynamic Programming in Knowledge Discovery for Rapid Response
One knowledge discovery problem in the rapid response setting is the cost of learning which patterns are indicative of a threat. This typically involves a detailed follow-through,...
Peter Frazier, Warren B. Powell, Savas Dayanik, Pa...
CDC
2010
IEEE
136views Control Systems» more  CDC 2010»
14 years 9 months ago
Pathologies of temporal difference methods in approximate dynamic programming
Approximate policy iteration methods based on temporal differences are popular in practice, and have been tested extensively, dating to the early nineties, but the associated conve...
Dimitri P. Bertsekas
156
Voted
RSS
2007
136views Robotics» more  RSS 2007»
15 years 4 months ago
The Stochastic Motion Roadmap: A Sampling Framework for Planning with Markov Motion Uncertainty
— We present a new motion planning framework that explicitly considers uncertainty in robot motion to maximize the probability of avoiding collisions and successfully reaching a ...
Ron Alterovitz, Thierry Siméon, Kenneth Y. ...
135
Voted
ACL
1998
15 years 3 months ago
Machine Translation with a Stochastic Grammatical Channel
We introduce a stochastic grammatical channel model for machine translation, that synthesizes several desirable characteristics of both statistical and grammatical machine transla...
Dekai Wu, Hongsing Wong
CSB
2004
IEEE
208views Bioinformatics» more  CSB 2004»
15 years 6 months ago
Pair Stochastic Tree Adjoining Grammars for Aligning and Predicting Pseudoknot RNA Structures
Motivation: Since the whole genome sequences for many species are currently available, computational predictions of RNA secondary structures and computational identifications of t...
Hiroshi Matsui, Kengo Sato, Yasubumi Sakakibara