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» Some Greedy Learning Algorithms for Sparse Regression and Cl...
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ICML
2008
IEEE
14 years 6 months ago
Sparse multiscale gaussian process regression
Most existing sparse Gaussian process (g.p.) models seek computational advantages by basing their computations on a set of m basis functions that are the covariance function of th...
Bernhard Schölkopf, Christian Walder, Kwang I...
JMLR
2006
156views more  JMLR 2006»
13 years 5 months ago
Large Scale Multiple Kernel Learning
While classical kernel-based learning algorithms are based on a single kernel, in practice it is often desirable to use multiple kernels. Lanckriet et al. (2004) considered conic ...
Sören Sonnenburg, Gunnar Rätsch, Christi...
ICCV
2003
IEEE
14 years 7 months ago
A Sparse Probabilistic Learning Algorithm for Real-Time Tracking
This paper addresses the problem of applying powerful pattern recognition algorithms based on kernels to efficient visual tracking. Recently Avidan [1] has shown that object recog...
Oliver M. C. Williams, Andrew Blake, Roberto Cipol...
ICMLA
2009
13 years 3 months ago
ECON: A Kernel Basis Pursuit Algorithm with Automatic Feature Parameter Tuning, and its Application to Photometric Solids Approx
This paper introduces a new algorithm, namely the EquiCorrelation Network (ECON), to perform supervised classification, and regression. ECON is a kernelized LARS-like algorithm, b...
Manuel Loth, Philippe Preux, Samuel Delepoulle, Ch...
ECML
2007
Springer
13 years 9 months ago
Ordinal Classification with Decision Rules
We consider the problem of ordinal classification, in which a value set of the decision attribute (output, dependent variable) is finite and ordered. This problem shares some chara...
Krzysztof Dembczynski, Wojciech Kotlowski, Roman S...