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» A Fast Learning Algorithm for Deep Belief Nets
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UAI
1997
13 years 9 months ago
Exploring Parallelism in Learning Belief Networks
It has been shown that a class of probabilistic domain models cannot be learned correctly by several existing algorithms which employ a single-link lookahead search. When a multil...
Tongsheng Chu, Yang Xiang
JMLR
2012
11 years 10 months ago
Online Incremental Feature Learning with Denoising Autoencoders
While determining model complexity is an important problem in machine learning, many feature learning algorithms rely on cross-validation to choose an optimal number of features, ...
Guanyu Zhou, Kihyuk Sohn, Honglak Lee
WWW
2007
ACM
14 years 8 months ago
Netprobe: a fast and scalable system for fraud detection in online auction networks
Given a large online network of online auction users and their histories of transactions, how can we spot anomalies and auction fraud? This paper describes the design and implemen...
Shashank Pandit, Duen Horng Chau, Samuel Wang, Chr...
NIPS
2003
13 years 9 months ago
Applying Metric-Trees to Belief-Point POMDPs
Recent developments in grid-based and point-based approximation algorithms for POMDPs have greatly improved the tractability of POMDP planning. These approaches operate on sets of...
Joelle Pineau, Geoffrey J. Gordon, Sebastian Thrun
CORR
2008
Springer
143views Education» more  CORR 2008»
13 years 7 months ago
Join Bayes Nets: A new type of Bayes net for relational data
Many real-world data are maintained in relational format, with different tables storing information about entities and their links or relationships. The structure (schema) of the ...
Oliver Schulte, Hassan Khosravi, Flavia Moser, Mar...