508 search results - page 33 / 102 » Learning for stochastic dynamic programming |
132
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ROBOCUP
2007
Springer
15 years 8 months ago
2007
Springer
Reinforcement learning is a paradigm under which an agent seeks to improve its policy by making learning updates based on the experiences it gathers through interaction with the en...
119
Voted
ECCV
2004
Springer
16 years 4 months ago
2004
Springer
We introduce a novel approach to modeling the dynamics of human facial motion induced by the action of speech for the purpose of synthesis. We represent the trajectories of a numbe...
117
Voted
ACL
2010
15 years 17 days ago
2010
Incremental parsing techniques such as shift-reduce have gained popularity thanks to their efficiency, but there remains a major problem: the search is greedy and only explores a ...
102
Voted
NIPS
2007
15 years 3 months ago
2007
The control of high-dimensional, continuous, non-linear dynamical systems is a key problem in reinforcement learning and control. Local, trajectory-based methods, using techniques...
125
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ICALT
2006
IEEE
15 years 8 months ago
2006
IEEE
It is difficult for a student to learn how to program and to build an understanding of the rationale which underpins the development of a program’s componentparts. Conventional ...