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ICML
2009
IEEE
15 years 11 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
16 years 5 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»
15 years 4 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»
14 years 11 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
16 years 5 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