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» Approximate Learning of Dynamic Models
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141
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JMLR
2006
124views more  JMLR 2006»
15 years 2 months ago
Policy Gradient in Continuous Time
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 ...
Rémi Munos
110
Voted
ACL
2010
15 years 20 days ago
Reading between the Lines: Learning to Map High-Level Instructions to Commands
In this paper, we address the task of mapping high-level instructions to sequences of commands in an external environment. Processing these instructions is challenging--they posit...
S. R. K. Branavan, Luke S. Zettlemoyer, Regina Bar...
135
Voted
CVPR
2006
IEEE
16 years 4 months ago
Dynamic Appearance Modeling for Human Tracking
Dynamic appearance is one of the most important cues for tracking and identifying moving people. However, direct modeling spatio-temporal variations of such appearance is often a ...
Hwasup Lim, Octavia I. Camps, Mario Sznaier, Vlad ...
124
Voted
FLAIRS
2007
15 years 5 months ago
Managing Dynamic Contexts Using Failure-Driven Stochastic Models
We describe an architecture for representing and managing context shifts that supports dynamic data interpretation. This architecture utilizes two layers of learning and three lay...
Nikita A. Sakhanenko, George F. Luger, Carl R. Ste...
103
Voted
ICML
2006
IEEE
16 years 3 months ago
Predictive linear-Gaussian models of controlled stochastic dynamical systems
We introduce the controlled predictive linearGaussian model (cPLG), a model that uses predictive state to model discrete-time dynamical systems with real-valued observations and v...
Matthew R. Rudary, Satinder P. Singh