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CORR
2012
Springer
235views Education» more  CORR 2012»
12 years 4 months ago
An Incremental Sampling-based Algorithm for Stochastic Optimal Control
Abstract— In this paper, we consider a class of continuoustime, continuous-space stochastic optimal control problems. Building upon recent advances in Markov chain approximation ...
Vu Anh Huynh, Sertac Karaman, Emilio Frazzoli
CVPR
2007
IEEE
14 years 10 months ago
Generative Graphical Models for Maneuvering Object Tracking and Dynamics Analysis
We study the challenging problem of maneuvering object tracking with unknown dynamics, i.e., forces or torque. We investigate the underlying causes of object kinematics, and propo...
Xin Fan, Guoliang Fan
TSP
2010
13 years 3 months ago
Learning Gaussian tree models: analysis of error exponents and extremal structures
The problem of learning tree-structured Gaussian graphical models from independent and identically distributed (i.i.d.) samples is considered. The influence of the tree structure a...
Vincent Y. F. Tan, Animashree Anandkumar, Alan S. ...
ICCV
2007
IEEE
14 years 10 months ago
Contour Grouping Based on Local Symmetry
The paper deals with grouping of edges to contours of shapes using only local symmetry and continuity. Shape skeletons are used to generate the search space for a version of the M...
Nagesh Adluru, Longin Jan Latecki, Rolf Lakäm...
CDC
2009
IEEE
132views Control Systems» more  CDC 2009»
14 years 1 months ago
Q-learning and Pontryagin's Minimum Principle
Abstract— Q-learning is a technique used to compute an optimal policy for a controlled Markov chain based on observations of the system controlled using a non-optimal policy. It ...
Prashant G. Mehta, Sean P. Meyn