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DAWAK
2010
Springer
15 years 6 months ago
Modelling Complex Data by Learning Which Variable to Construct
Abstract. This paper addresses a task of variable selection which consists in choosing a subset of variables that is sufficient to predict the target label well. Here instead of tr...
Françoise Fessant, Aurélie Le Cam, M...
COMSUR
2008
108views more  COMSUR 2008»
15 years 6 months ago
A survey of techniques for internet traffic classification using machine learning
The research community has begun looking for IP traffic classification techniques that do not rely on `well known' TCP or UDP port numbers, or interpreting the contents of pac...
Thuy T. T. Nguyen, Grenville J. Armitage
JMLR
2006
103views more  JMLR 2006»
15 years 6 months ago
MinReg: A Scalable Algorithm for Learning Parsimonious Regulatory Networks in Yeast and Mammals
In recent years, there has been a growing interest in applying Bayesian networks and their extensions to reconstruct regulatory networks from gene expression data. Since the gene ...
Dana Pe'er, Amos Tanay, Aviv Regev
NN
2006
Springer
127views Neural Networks» more  NN 2006»
15 years 6 months ago
The asymptotic equipartition property in reinforcement learning and its relation to return maximization
We discuss an important property called the asymptotic equipartition property on empirical sequences in reinforcement learning. This states that the typical set of empirical seque...
Kazunori Iwata, Kazushi Ikeda, Hideaki Sakai
NN
2006
Springer
114views Neural Networks» more  NN 2006»
15 years 6 months ago
Modular learning models in forecasting natural phenomena
Modular model is a particular type of committee machine and is comprised of a set of specialized (local) models each of which is responsible for a particular region of the input s...
Dimitri P. Solomatine, Michael Baskara L. A. Siek