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ICML
2009
IEEE
14 years 3 months ago
Using fast weights to improve persistent contrastive divergence
The most commonly used learning algorithm for restricted Boltzmann machines is contrastive divergence which starts a Markov chain at a data point and runs the chain for only a few...
Tijmen Tieleman, Geoffrey E. Hinton
ICML
2008
IEEE
14 years 9 months ago
Fast solvers and efficient implementations for distance metric learning
In this paper we study how to improve nearest neighbor classification by learning a Mahalanobis distance metric. We build on a recently proposed framework for distance metric lear...
Kilian Q. Weinberger, Lawrence K. Saul
BC
2005
71views more  BC 2005»
13 years 9 months ago
The spatiotemporal learning rule and its efficiency in separating spatiotemporal patterns
The hippocampus plays an important role in the course of establishing long-term memory, i.e., to make short-term memory of spatially and temporally associated input information. In...
M. Tsukada, X. Pan
JMLR
2010
101views more  JMLR 2010»
13 years 3 months ago
Efficient Reductions for Imitation Learning
Imitation Learning, while applied successfully on many large real-world problems, is typically addressed as a standard supervised learning problem, where it is assumed the trainin...
Stéphane Ross, Drew Bagnell
ICML
2007
IEEE
14 years 9 months ago
Learning for efficient retrieval of structured data with noisy queries
Increasingly large collections of structured data necessitate the development of efficient, noise-tolerant retrieval tools. In this work, we consider this issue and describe an ap...
Charles Parker, Alan Fern, Prasad Tadepalli