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NIPS
2007
15 years 8 months ago
Sparse Feature Learning for Deep Belief Networks
Unsupervised learning algorithms aim to discover the structure hidden in the data, and to learn representations that are more suitable as input to a supervised machine than the ra...
Marc'Aurelio Ranzato, Y-Lan Boureau, Yann LeCun
ICIC
2007
Springer
16 years 1 months ago
Fuzzy Modeling Via On-Line Clustering and Support Vector Machine
Abstract. This paper describes a novel fuzzy rule-based modeling approach for some slow industrial processses. Structure identification is realized by clustering and support vecto...
Julio César Tovar, Wen Yu, Xiaoou Li
NAACL
2007
15 years 8 months ago
Generation by Inverting a Semantic Parser that Uses Statistical Machine Translation
This paper explores the use of statistical machine translation (SMT) methods for tactical natural language generation. We present results on using phrase-based SMT for learning to...
Yuk Wah Wong, Raymond J. Mooney
NIPS
2001
15 years 8 months ago
Kernel Machines and Boolean Functions
We give results about the learnability and required complexity of logical formulae to solve classification problems. These results are obtained by linking propositional logic with...
Adam Kowalczyk, Alex J. Smola, Robert C. Williamso...
IJON
2011
169views more  IJON 2011»
15 years 1 months ago
Exploiting local structure in Boltzmann machines
Restricted Boltzmann Machines (RBM) are well-studied generative models. For image data, however, standard RBMs are suboptimal, since they do not exploit the local nature of image ...
Hannes Schulz, Andreas Müller 0004, Sven Behn...