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NN
2010
Springer
183views Neural Networks» more  NN 2010»
13 years 5 months ago
Dimensionality reduction for density ratio estimation in high-dimensional spaces
The ratio of two probability density functions is becoming a quantity of interest these days in the machine learning and data mining communities since it can be used for various d...
Masashi Sugiyama, Motoaki Kawanabe, Pui Ling Chui
ICPR
2008
IEEE
14 years 1 months ago
Spam filtering with several novel bayesian classifiers
In this paper, we report our work on spam filtering with three novel bayesian classification methods: Aggregating One-Dependence Estimators (AODE), Hidden Naïve Bayes (HNB), Loca...
Chuanliang Chen, Yingjie Tian, Chunhua Zhang
IJCNN
2006
IEEE
14 years 1 months ago
Automated Model Selection (AMS) on Finite Mixtures: A Theoretical Analysis
— From the Bayesian Ying-Yang (BYY) harmony learning theory, a harmony function has been developed for finite mixtures with a novel property that its maximization can make model...
Jinwen Ma
NECO
2011
13 years 2 months ago
Least-Squares Independent Component Analysis
Accurately evaluating statistical independence among random variables is a key element of Independent Component Analysis (ICA). In this paper, we employ a squared-loss variant of ...
Taiji Suzuki, Masashi Sugiyama
IDA
2009
Springer
14 years 2 months ago
Estimating Squared-Loss Mutual Information for Independent Component Analysis
Abstract. Accurately evaluating statistical independence among random variables is a key component of Independent Component Analysis (ICA). In this paper, we employ a squared-loss ...
Taiji Suzuki, Masashi Sugiyama