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» Feature-Discovering Approximate Value Iteration Methods
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TNN
1998
114views more  TNN 1998»
13 years 7 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»
13 years 7 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
13 years 9 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
14 years 2 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»
13 years 8 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