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UAI
1996
13 years 8 months ago
Bayesian Learning of Loglinear Models for Neural Connectivity
This paper presents a Bayesian approach to learning the connectivity structure of a group of neurons from data on configuration frequencies. A major objective of the research is t...
Kathryn B. Laskey, Laura Martignon
CIKM
2009
Springer
14 years 2 months ago
Reducing the risk of query expansion via robust constrained optimization
We introduce a new theoretical derivation, evaluation methods, and extensive empirical analysis for an automatic query expansion framework in which model estimation is cast as a r...
Kevyn Collins-Thompson
NPL
2002
168views more  NPL 2002»
13 years 7 months ago
Reduced Rank Kernel Ridge Regression
Ridge regression is a classical statistical technique that attempts to address the bias-variance trade-off in the design of linear regression models. A reformulation of ridge regr...
Gavin C. Cawley, Nicola L. C. Talbot
PADS
2003
ACM
14 years 22 days ago
Reducing the Size of Routing Tables for Large-scale Network Simulation
In simulating large-scale networks, due to the limitation of available resources on computers, the size of the networks and the scale of simulation scenarios are often restricted....
Akihito Hiromori, Hirozumi Yamaguchi, Keiichi Yasu...
GECCO
2004
Springer
116views Optimization» more  GECCO 2004»
14 years 26 days ago
Reducing Fitness Evaluations Using Clustering Techniques and Neural Network Ensembles
Abstract. In many real-world applications of evolutionary computation, it is essential to reduce the number of fitness evaluations. To this end, computationally efficient models c...
Yaochu Jin, Bernhard Sendhoff