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JMLR
2006
124views more  JMLR 2006»
15 years 4 months ago
A Direct Method for Building Sparse Kernel Learning Algorithms
Many kernel learning algorithms, including support vector machines, result in a kernel machine, such as a kernel classifier, whose key component is a weight vector in a feature sp...
Mingrui Wu, Bernhard Schölkopf, Gökhan H...
ORL
2008
93views more  ORL 2008»
15 years 4 months ago
Polymatroids and mean-risk minimization in discrete optimization
We study discrete optimization problems with a submodular mean-risk minimization objective. For 0-1 problems a linear characterization of the convex lower envelope is given. For mi...
Alper Atamtürk, Vishnu Narayanan
HSNMC
2004
Springer
126views Multimedia» more  HSNMC 2004»
15 years 10 months ago
Hybrid Unicast and Multicast Flow Control: A Linear Optimization Approach
— In this paper, we present a solution to the general problem of flow control for both unicast and multicast IP networks. We formulate a convex optimization problem that can be ...
Homayoun Yousefi'zadeh, Fatemeh Fazel, Hamid Jafar...
CVPR
2010
IEEE
16 years 27 days ago
Simultaneous Point Matching and 3D Deformable Surface Reconstruction
It has been shown that the 3D shape of a deformable surface in an image can be recovered by establishing correspondences between that image and a reference one in which the shape ...
Appu Shaji, Aydin Varol, Lorenzo Torresani, Pascal...
JMLR
2012
13 years 7 months ago
A General Framework for Structured Sparsity via Proximal Optimization
We study a generalized framework for structured sparsity. It extends the well known methods of Lasso and Group Lasso by incorporating additional constraints on the variables as pa...
Luca Baldassarre, Jean Morales, Andreas Argyriou, ...