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» Fractional Kernels in Digraphs
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117
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TNN
2010
176views Management» more  TNN 2010»
14 years 6 months ago
Sparse approximation through boosting for learning large scale kernel machines
Abstract--Recently, sparse approximation has become a preferred method for learning large scale kernel machines. This technique attempts to represent the solution with only a subse...
Ping Sun, Xin Yao
92
Voted
NIPS
2003
15 years 1 months ago
Sparseness of Support Vector Machines---Some Asymptotically Sharp Bounds
The decision functions constructed by support vector machines (SVM’s) usually depend only on a subset of the training set—the so-called support vectors. We derive asymptotical...
Ingo Steinwart
CORR
2008
Springer
375views Education» more  CORR 2008»
14 years 11 months ago
The Margitron: A Generalised Perceptron with Margin
We identify the classical Perceptron algorithm with margin as a member of a broader family of large margin classifiers which we collectively call the Margitron. The Margitron, (des...
Constantinos Panagiotakopoulos, Petroula Tsampouka
77
Voted
SODA
2010
ACM
143views Algorithms» more  SODA 2010»
14 years 10 months ago
Thin Partitions: Isoperimetric Inequalities and a Sampling Algorithm for Star Shaped Bodies
Star-shaped bodies are an important nonconvex generalization of convex bodies (e.g., linear programming with violations). Here we present an efficient algorithm for sampling a giv...
Karthekeyan Chandrasekaran, Daniel Dadush, Santosh...
PAMI
2006
132views more  PAMI 2006»
14 years 11 months ago
Capitalize on Dimensionality Increasing Techniques for Improving Face Recognition Grand Challenge Performance
This paper presents a novel pattern recognition framework by capitalizing on dimensionality increasing techniques. In particular, the framework integrates Gabor image representatio...
Chengjun Liu