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UAI
2008
15 years 1 months ago
Projected Subgradient Methods for Learning Sparse Gaussians
Gaussian Markov random fields (GMRFs) are useful in a broad range of applications. In this paper we tackle the problem of learning a sparse GMRF in a high-dimensional space. Our a...
John Duchi, Stephen Gould, Daphne Koller
CAL
2004
14 years 11 months ago
An Efficient Fault-Tolerant Routing Methodology for Meshes and Tori
In this paper we present a methodology to design fault-tolerant routing algorithms for regular direct interconnection networks. It supports fully adaptive routing, does not degrade...
María Engracia Gómez, José Du...
ML
2007
ACM
14 years 11 months ago
Feature space perspectives for learning the kernel
In this paper, we continue our study of learning an optimal kernel in a prescribed convex set of kernels, [18]. We present a reformulation of this problem within a feature space e...
Charles A. Micchelli, Massimiliano Pontil
MP
2011
14 years 2 months ago
Strong KKT conditions and weak sharp solutions in convex-composite optimization
Using variational analysis techniques, we study convex-composite optimization problems. In connection with such a problem, we introduce several new notions as variances of the clas...
Xi Yin Zheng, Kung Fu Ng
MP
2011
14 years 2 months ago
Implicit solution function of P0 and Z matrix linear complementarity constraints
Abstract. Using the least element solution of the P0 and Z matrix linear complementarity problem (LCP), we define an implicit solution function for linear complementarity constrai...
Xiaojun Chen, Shuhuang Xiang