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TNN
2008
152views more  TNN 2008»
13 years 7 months ago
Distributed Parallel Support Vector Machines in Strongly Connected Networks
We propose a distributed parallel support vector machine (DPSVM) training mechanism in a configurable network environment for distributed data mining. The basic idea is to exchange...
Yumao Lu, Vwani P. Roychowdhury, L. Vandenberghe
TIP
2010
127views more  TIP 2010»
13 years 5 months ago
Bayesian Compressive Sensing Using Laplace Priors
In this paper we model the components of the compressive sensing (CS) problem, i.e., the signal acquisition process, the unknown signal coefficients and the model parameters for ...
S. Derin Babacan, Rafael Molina, Aggelos K. Katsag...
TCBB
2011
13 years 2 months ago
Accurate Construction of Consensus Genetic Maps via Integer Linear Programming
—We study the problem of merging genetic maps, when the individual genetic maps are given as directed acyclic graphs. The computational problem is to build a consensus map, which...
Yonghui Wu, Timothy J. Close, Stefano Lonardi
JMLR
2010
149views more  JMLR 2010»
13 years 2 months ago
Learning Bayesian Network Structure using LP Relaxations
We propose to solve the combinatorial problem of finding the highest scoring Bayesian network structure from data. This structure learning problem can be viewed as an inference pr...
Tommi Jaakkola, David Sontag, Amir Globerson, Mari...
SIAMSC
2010
155views more  SIAMSC 2010»
13 years 2 months ago
Quasi-Newton Methods on Grassmannians and Multilinear Approximations of Tensors
In this paper we proposed quasi-Newton and limited memory quasi-Newton methods for objective functions defined on Grassmannians or a product of Grassmannians. Specifically we defin...
Berkant Savas, Lek-Heng Lim