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CIKM
2011
Springer
14 years 7 months ago
Towards feature selection in network
Traditional feature selection methods assume that the data are independent and identically distributed (i.i.d.). In real world, tremendous amounts of data are distributed in a net...
Quanquan Gu, Jiawei Han
ICDM
2007
IEEE
289views Data Mining» more  ICDM 2007»
16 years 1 months ago
Latent Dirichlet Conditional Naive-Bayes Models
In spite of the popularity of probabilistic mixture models for latent structure discovery from data, mixture models do not have a natural mechanism for handling sparsity, where ea...
Arindam Banerjee, Hanhuai Shan
CSDA
2007
106views more  CSDA 2007»
15 years 7 months ago
Parsimonious additive models
A new method for function estimation and variable selection, specifically designed for additive models fitted by cubic splines is proposed.This new method involves regularizing ...
Marta Avalos, Yves Grandvalet, Christophe Ambroise
ICLP
2009
Springer
16 years 8 months ago
Preprocessing for Optimization of Probabilistic-Logic Models for Sequence Analysis
Abstract. A class of probabilistic-logic models is considered, which increases the expressibility from HMM's and SCFG's regular and contextfree languages to, in principle...
Henning Christiansen, Ole Torp Lassen
NIPS
2004
15 years 9 months ago
Hierarchical Distributed Representations for Statistical Language Modeling
Statistical language models estimate the probability of a word occurring in a given context. The most common language models rely on a discrete enumeration of predictive contexts ...
John Blitzer, Kilian Q. Weinberger, Lawrence K. Sa...