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UAI
2008
13 years 9 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
13 years 8 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
13 years 7 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
12 years 11 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
12 years 11 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