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» A Kernel Method for the Two-Sample Problem
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JMLR
2006
116views more  JMLR 2006»
15 years 2 months ago
Step Size Adaptation in Reproducing Kernel Hilbert Space
This paper presents an online support vector machine (SVM) that uses the stochastic meta-descent (SMD) algorithm to adapt its step size automatically. We formulate the online lear...
S. V. N. Vishwanathan, Nicol N. Schraudolph, Alex ...
129
Voted
IPPS
2007
IEEE
15 years 9 months ago
Experience of Optimizing FFT on Intel Architectures
Automatic library generators, such as ATLAS [11], Spiral [8] and FFTW [2], are promising technologies to generate efficient code for different computer architectures. The library...
Daniel Orozco, Liping Xue, Murat Bolat, Xiaoming L...
110
Voted
ISNN
2005
Springer
15 years 8 months ago
Multiple Parameter Selection for LS-SVM Using Smooth Leave-One-Out Error
In least squares support vector (LS-SVM), the key challenge lies in the selection of free parameters such as kernel parameters and tradeoff parameter. However, when a large number ...
Liefeng Bo, Ling Wang, Licheng Jiao
110
Voted
ICML
2010
IEEE
15 years 3 months ago
On Sparse Nonparametric Conditional Covariance Selection
We develop a penalized kernel smoothing method for the problem of selecting nonzero elements of the conditional precision matrix, known as conditional covariance selection. This p...
Mladen Kolar, Ankur P. Parikh, Eric P. Xing
105
Voted
PDPTA
2003
15 years 3 months ago
A Universal Parallel SAT Checking Kernel
We present a novel approach to parallel Boolean satisfiability (SAT) checking. A distinctive feature of our parallel SAT checker is that it incorporates all essential heuristics ...
Wolfgang Blochinger, Carsten Sinz, Wolfgang Kü...