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ICML
1995
IEEE
16 years 7 months ago
Stable Function Approximation in Dynamic Programming
The success ofreinforcement learninginpractical problems depends on the ability to combine function approximation with temporal di erence methods such as value iteration. Experime...
Geoffrey J. Gordon
NN
2006
Springer
153views Neural Networks» more  NN 2006»
15 years 6 months ago
An incremental network for on-line unsupervised classification and topology learning
This paper presents an on-line unsupervised learning mechanism for unlabeled data that are polluted by noise. Using a similarity thresholdbased and a local error-based insertion c...
Shen Furao, Osamu Hasegawa
CORR
2011
Springer
151views Education» more  CORR 2011»
15 years 1 months ago
A supervised clustering approach for fMRI-based inference of brain states
We propose a method that combines signals from many brain regions observed in functional Magnetic Resonance Imaging (fMRI) to predict the subject’s behavior during a scanning se...
Vincent Michel, Alexandre Gramfort, Gaël Varo...
COLT
2010
Springer
15 years 4 months ago
Adaptive Subgradient Methods for Online Learning and Stochastic Optimization
We present a new family of subgradient methods that dynamically incorporate knowledge of the geometry of the data observed in earlier iterations to perform more informative gradie...
John Duchi, Elad Hazan, Yoram Singer
AUSAI
2008
Springer
15 years 8 months ago
L-Diversity Based Dynamic Update for Large Time-Evolving Microdata
Data anonymization techniques based on enhanced privacy principles have been the focus of intense research in the last few years. All existing methods achieving privacy principles ...
Xiaoxun Sun, Hua Wang, Jiuyong Li