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GECCO
2008
Springer
118views Optimization» more  GECCO 2008»
15 years 7 months ago
Unsupervised learning of echo state networks: balancing the double pole
A possible alternative to fine topology tuning for Neural Network (NN) optimization is to use Echo State Networks (ESNs), recurrent NNs built upon a large reservoir of sparsely r...
Fei Jiang, Hugues Berry, Marc Schoenauer
COR
2008
142views more  COR 2008»
15 years 6 months ago
Application of reinforcement learning to the game of Othello
Operations research and management science are often confronted with sequential decision making problems with large state spaces. Standard methods that are used for solving such c...
Nees Jan van Eck, Michiel C. van Wezel
KDD
2010
ACM
274views Data Mining» more  KDD 2010»
15 years 10 months ago
Grafting-light: fast, incremental feature selection and structure learning of Markov random fields
Feature selection is an important task in order to achieve better generalizability in high dimensional learning, and structure learning of Markov random fields (MRFs) can automat...
Jun Zhu, Ni Lao, Eric P. Xing
ICDE
2012
IEEE
221views Database» more  ICDE 2012»
13 years 8 months ago
DPCube: Releasing Differentially Private Data Cubes for Health Information
—We demonstrate DPCube, a component in our Health Information DE-identification (HIDE) framework, for releasing differentially private data cubes (or multi-dimensional histogram...
Yonghui Xiao, James J. Gardner, Li Xiong
ICML
2003
IEEE
16 years 7 months ago
BL-WoLF: A Framework For Loss-Bounded Learnability In Zero-Sum Games
We present BL-WoLF, a framework for learnability in repeated zero-sum games where the cost of learning is measured by the losses the learning agent accrues (rather than the number...
Vincent Conitzer, Tuomas Sandholm