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ESANN
2007
13 years 10 months ago
Model Selection for Kernel Probit Regression
Abstract. The convex optimisation problem involved in fitting a kernel probit regression (KPR) model can be solved efficiently via an iteratively re-weighted least-squares (IRWLS)...
Gavin C. Cawley
SODA
2001
ACM
110views Algorithms» more  SODA 2001»
13 years 9 months ago
Improved approximation algorithms for rectangle tiling and packing
We provide improved approximation algorithms for several rectangle tiling and packing problems (RTILE, DRTILE and d-RPACK) studied in the literature. Our algorithms are highly eff...
Piotr Berman, Bhaskar DasGupta, S. Muthukrishnan, ...
CVPR
2012
IEEE
11 years 11 months ago
Boosting algorithms for simultaneous feature extraction and selection
The problem of simultaneous feature extraction and selection, for classifier design, is considered. A new framework is proposed, based on boosting algorithms that can either 1) s...
Mohammad J. Saberian, Nuno Vasconcelos
TSP
2008
115views more  TSP 2008»
13 years 8 months ago
Approximation Bounds for Semidefinite Relaxation of Max-Min-Fair Multicast Transmit Beamforming Problem
Consider a downlink multicast scenario where a base station equipped with multiple antennas wishes to simultaneously broadcast a number of signals to some given groups of users ove...
Tsung-Hui Chang, Zhi-Quan Luo, Chong-Yung Chi
CORR
2010
Springer
100views Education» more  CORR 2010»
13 years 8 months ago
Convex Relaxations for Subset Selection
We use convex relaxation techniques to produce lower bounds on the optimal value of subset selection problems and generate good approximate solutions. We then explicitly bound the...
Francis Bach, Selin Damla Ahipasaoglu, Alexandre d...