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» A Kernel Method for the Two-Sample Problem
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JMLR
2002
137views more  JMLR 2002»
15 years 2 months ago
The Subspace Information Criterion for Infinite Dimensional Hypothesis Spaces
A central problem in learning is selection of an appropriate model. This is typically done by estimating the unknown generalization errors of a set of models to be selected from a...
Masashi Sugiyama, Klaus-Robert Müller
164
Voted
CVPR
2009
IEEE
15 years 5 months ago
Nonlinear Nonnegative Component Analysis
In this paper general solutions for Nonlinear Nonnegative Component Analysis for data representation and recognition are proposed. That is, motivated by a combination of the Nonne...
Stefanos Zafeiriou, Maria Petrou
WWW
2006
ACM
16 years 3 months ago
A web-based kernel function for measuring the similarity of short text snippets
Determining the similarity of short text snippets, such as search queries, works poorly with traditional document similarity measures (e.g., cosine), since there are often few, if...
Mehran Sahami, Timothy D. Heilman
107
Voted
TSMC
2008
99views more  TSMC 2008»
15 years 2 months ago
Robust Regularized Kernel Regression
Robust regression techniques are critical to fitting data with noise in real-world applications. Most previous work of robust kernel regression is usually formulated into a dual fo...
Jianke Zhu, Steven C. H. Hoi, Michael R. Lyu
147
Voted
PAMI
2011
14 years 9 months ago
Multiple Kernel Learning for Dimensionality Reduction
—In solving complex visual learning tasks, adopting multiple descriptors to more precisely characterize the data has been a feasible way for improving performance. The resulting ...
Yen-Yu Lin, Tyng-Luh Liu, Chiou-Shann Fuh