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CVPR
2010
IEEE
14 years 6 months ago
Learning Shift-Invariant Sparse Representation of Actions
A central problem in the analysis of motion capture (Mo- Cap) data is how to decompose motion sequences into primitives. Ideally, a description in terms of primitives should fac...
Yi Li
WECWIS
2003
IEEE
120views ECommerce» more  WECWIS 2003»
14 years 3 months ago
Reinforcement Learning Applications in Dynamic Pricing of Retail Markets
In this paper, we investigate the use of reinforcement learning (RL) techniques to the problem of determining dynamic prices in an electronic retail market. As representative mode...
C. V. L. Raju, Y. Narahari, K. Ravikumar
CSR
2007
Springer
14 years 4 months ago
New Bounds for MAX-SAT by Clause Learning
To solve a problem on a given CNF formula F a splitting algorithm recursively calls for F[v] and F[¬v] for a variable v. Obviously, after the first call an algorithm obtains some...
Alexander S. Kulikov, Konstantin Kutzkov
CVPR
2011
IEEE
13 years 5 months ago
Learning Temporally Consistent Rigidities
We present a novel probabilistic framework for rigid tracking and segmentation of shapes observed from multiple cameras. Most existing methods have focused on solving each of thes...
Jean-Sebastien Franco, Edmond Boyer
ICML
2009
IEEE
14 years 11 months ago
Discovering options from example trajectories
We present a novel technique for automated problem decomposition to address the problem of scalability in reinforcement learning. Our technique makes use of a set of near-optimal ...
Peng Zang, Peng Zhou, David Minnen, Charles Lee Is...