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DIS
2006
Springer
15 years 8 months ago
Optimal Bayesian 2D-Discretization for Variable Ranking in Regression
In supervised machine learning, variable ranking aims at sorting the input variables according to their relevance w.r.t. an output variable. In this paper, we propose a new relevan...
Marc Boullé, Carine Hue
NIPS
2007
15 years 5 months ago
HM-BiTAM: Bilingual Topic Exploration, Word Alignment, and Translation
We present a novel paradigm for statistical machine translation (SMT), based on a joint modeling of word alignment and the topical aspects underlying bilingual document-pairs, via...
Bing Zhao, Eric P. Xing
NIPS
2003
15 years 5 months ago
Extreme Components Analysis
Principal components analysis (PCA) is one of the most widely used techniques in machine learning and data mining. Minor components analysis (MCA) is less well known, but can also...
Max Welling, Felix V. Agakov, Christopher K. I. Wi...
DATAMINE
2010
122views more  DATAMINE 2010»
15 years 4 months ago
Three naive Bayes approaches for discrimination-free classification
In this paper, we investigate how to modify the Naive Bayes classifier in order to perform classification that is restricted to be independent with respect to a given sensitive att...
Toon Calders, Sicco Verwer
PAMI
2010
192views more  PAMI 2010»
15 years 2 months ago
Multiway Spectral Clustering with Out-of-Sample Extensions through Weighted Kernel PCA
—A new formulation for multiway spectral clustering is proposed. This method corresponds to a weighted kernel principal component analysis (PCA) approach based on primal-dual lea...
Carlos Alzate, Johan A. K. Suykens