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» A Constraint Learning Algorithm for Blind Source Separation
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ICML
2005
IEEE
14 years 8 months ago
Building Sparse Large Margin Classifiers
This paper presents an approach to build Sparse Large Margin Classifiers (SLMC) by adding one more constraint to the standard Support Vector Machine (SVM) training problem. The ad...
Bernhard Schölkopf, Gökhan H. Bakir, Min...
AAAI
2012
11 years 10 months ago
Transfer Learning with Graph Co-Regularization
Transfer learning proves to be effective for leveraging labeled data in the source domain to build an accurate classifier in the target domain. The basic assumption behind transf...
Mingsheng Long, Jianmin Wang 0001, Guiguang Ding, ...
NIPS
2003
13 years 9 months ago
Computing Gaussian Mixture Models with EM Using Equivalence Constraints
Density estimation with Gaussian Mixture Models is a popular generative technique used also for clustering. We develop a framework to incorporate side information in the form of e...
Noam Shental, Aharon Bar-Hillel, Tomer Hertz, Daph...
MM
2003
ACM
105views Multimedia» more  MM 2003»
14 years 29 days ago
Universal synchronization scheme for distributed audio-video capture on heterogeneous computing platforms
We propose a universal synchronization scheme for distributed audio-video capture on heterogeneous computing devices such as laptops, tablets, PDAs, cellular phones, audio recorde...
Rainer Lienhart, Igor Kozintsev, Stefan Wehr
DATAMINE
2006
130views more  DATAMINE 2006»
13 years 7 months ago
Mining Adaptive Ratio Rules from Distributed Data Sources
Different from traditional association-rule mining, a new paradigm called Ratio Rule (RR) was proposed recently. Ratio rules are aimed at capturing the quantitative association kno...
Jun Yan, Ning Liu, Qiang Yang, Benyu Zhang, QianSh...