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ATAL
2006
Springer
15 years 10 months ago
Learning to identify winning coalitions in the PAC model
We consider PAC learning of simple cooperative games, in which the coalitions are partitioned into "winning" and "losing" coalitions. We analyze the complexity...
Ariel D. Procaccia, Jeffrey S. Rosenschein
IDEAL
2005
Springer
16 years 2 days ago
Cluster Analysis of High-Dimensional Data: A Case Study
Abstract. Normal mixture models are often used to cluster continuous data. However, conventional approaches for fitting these models will have problems in producing nonsingular es...
Richard Bean, Geoffrey J. McLachlan
CSDA
2006
304views more  CSDA 2006»
15 years 6 months ago
Using principal components for estimating logistic regression with high-dimensional multicollinear data
The logistic regression model is used to predict a binary response variable in terms of a set of explicative ones. The estimation of the model parameters is not too accurate and t...
Ana M. Aguilera, Manuel Escabias, Mariano J. Valde...
EC
2010
176views ECommerce» more  EC 2010»
15 years 4 months ago
Learning Factorizations in Estimation of Distribution Algorithms Using Affinity Propagation
Estimation of distribution algorithms (EDAs) that use marginal product model factorizations have been widely applied to a broad range of, mainly binary, optimization problems. In ...
Roberto Santana, Pedro Larrañaga, Jos&eacut...
NN
1998
Springer
108views Neural Networks» more  NN 1998»
15 years 6 months ago
How embedded memory in recurrent neural network architectures helps learning long-term temporal dependencies
Learning long-term temporal dependencies with recurrent neural networks can be a difficult problem. It has recently been shown that a class of recurrent neural networks called NA...
Tsungnan Lin, Bill G. Horne, C. Lee Giles