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IJCAI
2007
13 years 11 months ago
Bayesian Inverse Reinforcement Learning
Inverse Reinforcement Learning (IRL) is the problem of learning the reward function underlying a Markov Decision Process given the dynamics of the system and the behaviour of an e...
Deepak Ramachandran, Eyal Amir
AMC
2010
111views more  AMC 2010»
13 years 10 months ago
Algebraic C*-actions and the inverse kinematics of a general 6R manipulator
Let X be a smooth quadric of dimension 2m in P2m+1 C and let Y, Z X be subvarieties both of dimension m which intersect transversely. In this paper we give an algorithm for comput...
Sandra Di Rocco, David Eklund, Andrew J. Sommese, ...
TVCG
2008
167views more  TVCG 2008»
13 years 8 months ago
Optimal Surface Parameterization Using Inverse Curvature Map
Mesh parameterization is a fundamental technique in computer graphics. The major goals during mesh parameterization are to minimize both the angle distortion and the area distortio...
Yong-Liang Yang, Junho Kim, Feng Luo 0002, Shi-Min...
CVPR
2008
IEEE
14 years 12 months ago
Dimensionality reduction using covariance operator inverse regression
We consider the task of dimensionality reduction for regression (DRR) whose goal is to find a low dimensional representation of input covariates, while preserving the statistical ...
Minyoung Kim, Vladimir Pavlovic
COMPUTING
2007
122views more  COMPUTING 2007»
13 years 10 months ago
Error estimation for Bregman iterations and inverse scale space methods in image restoration
In this paper we consider error estimation for image restoration problems based on generalized Bregman distances. This error estimation technique has been used to derive convergen...
Martin Burger, E. Resmerita, Lin He