509 search results - page 29 / 102 » Using Learning for Approximation in Stochastic Processes |
110
Voted
EACL
2006
ACL Anthology
15 years 4 months ago
2006
ACL Anthology
In this paper we extend the maximum spanning tree (MST) dependency parsing framework of McDonald et al. (2005c) to incorporate higher-order feature representations and allow depen...
114
Voted
ICIP
2010
IEEE
15 years 15 days ago
2010
IEEE
Optical lithography is a critical step in the semiconductor manufacturing process, and one key problem is the design of the photomask for a particular circuit pattern, given the o...
117
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HYBRID
2004
Springer
15 years 8 months ago
2004
Springer
We propose a model for Stochastic Hybrid Systems (SHSs) where transitions between discrete modes are triggered by stochastic events much like transitions between states of a contin...
123
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ECML
2006
Springer
15 years 6 months ago
2006
Springer
Abstract. Approximate Policy Iteration (API) is a reinforcement learning paradigm that is able to solve high-dimensional, continuous control problems. We propose to exploit API for...
141
Voted
JMLR
2006
15 years 2 months ago
2006
Policy search is a method for approximately solving an optimal control problem by performing a parametric optimization search in a given class of parameterized policies. In order ...