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» Outlier Detection with Kernel Density Functions
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NN
2010
Springer
183views Neural Networks» more  NN 2010»
13 years 4 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
ICIP
2009
IEEE
13 years 4 months ago
Object tracking by bidirectional learning with feature selection
This paper proposes a new tracking algorithm which combines object and background information, via building object and background appearance models simultaneously by nonparametric...
Heng Wang, Xinwen Hou, Cheng-Lin Liu
ML
2012
ACM
388views Machine Learning» more  ML 2012»
12 years 1 months ago
Statistical analysis of kernel-based least-squares density-ratio estimation
The ratio of two probability densities can be used for solving various machine learning tasks such as covariate shift adaptation (importance sampling), outlier detection (likeliho...
Takafumi Kanamori, Taiji Suzuki, Masashi Sugiyama
ICA
2007
Springer
14 years 12 days ago
Robust Independent Component Analysis Using Quadratic Negentropy
We present a robust algorithm for independent component analysis that uses the sum of marginal quadratic negentropies as a dependence measure. It can handle arbitrary source densit...
Jaehyung Lee, Taesu Kim, Soo-Young Lee
WCRE
2008
IEEE
14 years 19 days ago
An Empirical Study of Function Clones in Open Source Software
The new hybrid clone detection tool NICAD combines the strengths and overcomes the limitations of both textbased and AST-based clone detection techniques to yield highly accurate ...
Chanchal Kumar Roy, James R. Cordy