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» Using Learning for Approximation in Stochastic Processes
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NIPS
2001
13 years 8 months ago
Predictive Representations of State
We show that states of a dynamical system can be usefully represented by multi-step, action-conditional predictions of future observations. State representations that are grounded...
Michael L. Littman, Richard S. Sutton, Satinder P....
ICA
2007
Springer
13 years 11 months ago
Phase-Aware Non-negative Spectrogram Factorization
Non-negative spectrogram factorization has been proposed for single-channel source separation tasks. These methods operate on the magnitude or power spectrogram of the input mixtur...
R. Mitchell Parry, Irfan A. Essa
SDM
2011
SIAM
232views Data Mining» more  SDM 2011»
12 years 10 months ago
A Sequential Dual Method for Structural SVMs
In many real world prediction problems the output is a structured object like a sequence or a tree or a graph. Such problems range from natural language processing to computationa...
Shirish Krishnaj Shevade, Balamurugan P., S. Sunda...
KDD
2008
ACM
178views Data Mining» more  KDD 2008»
14 years 7 months ago
Training structural svms with kernels using sampled cuts
Discriminative training for structured outputs has found increasing applications in areas such as natural language processing, bioinformatics, information retrieval, and computer ...
Chun-Nam John Yu, Thorsten Joachims
KDD
2004
ACM
156views Data Mining» more  KDD 2004»
14 years 7 months ago
TiVo: making show recommendations using a distributed collaborative filtering architecture
We describe the TiVo television show collaborative recommendation system which has been fielded in over one million TiVo clients for four years. Over this install base, TiVo curre...
Kamal Ali, Wijnand van Stam