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» Feature-Discovering Approximate Value Iteration Methods
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TNN
1998
114views more  TNN 1998»
14 years 9 months ago
Bayesian retrieval in associative memories with storage errors
Abstract—It is well known that for finite-sized networks, onestep retrieval in the autoassociative Willshaw net is a suboptimal way to extract the information stored in the syna...
Friedrich T. Sommer, Peter Dayan
JMLR
2008
168views more  JMLR 2008»
14 years 9 months ago
Max-margin Classification of Data with Absent Features
We consider the problem of learning classifiers in structured domains, where some objects have a subset of features that are inherently absent due to complex relationships between...
Gal Chechik, Geremy Heitz, Gal Elidan, Pieter Abbe...
ICMLA
2008
14 years 11 months ago
Basis Function Construction in Reinforcement Learning Using Cascade-Correlation Learning Architecture
In reinforcement learning, it is a common practice to map the state(-action) space to a different one using basis functions. This transformation aims to represent the input data i...
Sertan Girgin, Philippe Preux
ATAL
2009
Springer
15 years 4 months ago
Directed soft arc consistency in pseudo trees
We propose an efficient method that applies directed soft arc consistency to a Distributed Constraint Optimization Problem (DCOP) which is a fundamental framework of multi-agent ...
Toshihiro Matsui, Marius-Calin Silaghi, Katsutoshi...
CORR
2008
Springer
92views Education» more  CORR 2008»
14 years 9 months ago
Nonnegative Matrix Factorization via Rank-One Downdate
Nonnegative matrix factorization (NMF) was popularized as a tool for data mining by Lee and Seung in 1999. NMF attempts to approximate a matrix with nonnegative entries by a produ...
Michael Biggs, Ali Ghodsi, Stephen A. Vavasis