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ICIP
2006
IEEE
16 years 7 months ago
Local Discriminant Embedding with Tensor Representation
We present a subspace learning method, called Local Discriminant Embedding with Tensor representation (LDET), that addresses simultaneously the generalization and data representat...
Jian Xia, Dit-Yan Yeung, Guang Dai
ECSQARU
2009
Springer
16 years 15 days ago
Probability Density Estimation by Perturbing and Combining Tree Structured Markov Networks
To explore the Perturb and Combine idea for estimating probability densities, we study mixtures of tree structured Markov networks derived by bagging combined with the Chow and Liu...
Sourour Ammar, Philippe Leray, Boris Defourny, Lou...
AMAI
2004
Springer
15 years 11 months ago
New Look-Ahead Schemes for Constraint Satisfaction
This paper presents new look-ahead schemes for backtracking search when solving constraint satisfaction problems. The look-ahead schemes compute a heuristic for value ordering and...
Kalev Kask, Rina Dechter, Vibhav Gogate
ATAL
2004
Springer
15 years 11 months ago
Approximate Solutions for Partially Observable Stochastic Games with Common Payoffs
Partially observable decentralized decision making in robot teams is fundamentally different from decision making in fully observable problems. Team members cannot simply apply si...
Rosemary Emery-Montemerlo, Geoffrey J. Gordon, Jef...
GECCO
2010
Springer
195views Optimization» more  GECCO 2010»
15 years 10 months ago
Improved step size adaptation for the MO-CMA-ES
The multi-objective covariance matrix adaptation evolution strategy (MO-CMA-ES) is an evolutionary algorithm for continuous vector-valued optimization. It combines indicator-based...
Thomas Voß, Nikolaus Hansen, Christian Igel