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NIPS
2007
15 years 8 months ago
Stable Dual Dynamic Programming
Recently, we have introduced a novel approach to dynamic programming and reinforcement learning that is based on maintaining explicit representations of stationary distributions i...
Tao Wang, Daniel J. Lizotte, Michael H. Bowling, D...
IJON
1998
158views more  IJON 1998»
15 years 7 months ago
Bayesian Kullback Ying-Yang dependence reduction theory
Bayesian Kullback Ying—Yang dependence reduction system and theory is presented. Via stochastic approximation, implementable algorithms and criteria are given for parameter lear...
Lei Xu
SIAMJO
2010
125views more  SIAMJO 2010»
15 years 2 months ago
Trading Accuracy for Sparsity in Optimization Problems with Sparsity Constraints
We study the problem of minimizing the expected loss of a linear predictor while constraining its sparsity, i.e., bounding the number of features used by the predictor. While the r...
Shai Shalev-Shwartz, Nathan Srebro, Tong Zhang
IROS
2007
IEEE
171views Robotics» more  IROS 2007»
16 years 1 months ago
Learning full-body motions from monocular vision: dynamic imitation in a humanoid robot
— In an effort to ease the burden of programming motor commands for humanoid robots, a computer vision technique is developed for converting a monocular video sequence of human p...
Jeffrey B. Cole, David B. Grimes, Rajesh P. N. Rao
CIG
2005
IEEE
16 years 27 days ago
Further Evolution of a Self-Learning Chess Program
Previous research on the use of coevolution to improve a baseline chess program demonstrated a performance rating of 2550 against Pocket Fritz 2.0 (PF2). A series of 12 games (6 wh...
David B. Fogel, Timothy J. Hays, Sarah L. Hahn, Ja...