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JMLR
2010
161views more  JMLR 2010»
14 years 11 months ago
Dual Averaging Methods for Regularized Stochastic Learning and Online Optimization
We consider regularized stochastic learning and online optimization problems, where the objective function is the sum of two convex terms: one is the loss function of the learning...
Lin Xiao
CORR
2011
Springer
204views Education» more  CORR 2011»
14 years 11 months ago
Accelerated Dual Descent for Network Optimization
—Dual descent methods are commonly used to solve network optimization problems because their implementation can be distributed through the network. However, their convergence rat...
Michael Zargham, A. Ribeiro, Ali Jadbabaie, Asuman...
ICASSP
2011
IEEE
14 years 8 months ago
A-Functions: A generalization of Extended Baum-Welch transformations to convex optimization
We introduce the Line Search A-Function (LSAF) technique that generalizes the Extended-Baum Welch technique in order to provide an effective optimization technique for a broader s...
Dimitri Kanevsky, David Nahamoo, Tara N. Sainath, ...
CVPR
2004
IEEE
16 years 6 months ago
Optimizing Motion Estimation with Linear Programming and Detail-Preserving Variational Method
In this paper, we propose a novel linear programming based method to estimate arbitrary motion from two images. The proposed method always finds the global optimal solution of the...
Hao Jiang, Ze-Nian Li, Mark S. Drew
ICLP
2009
Springer
16 years 5 months ago
Preprocessing for Optimization of Probabilistic-Logic Models for Sequence Analysis
Abstract. A class of probabilistic-logic models is considered, which increases the expressibility from HMM's and SCFG's regular and contextfree languages to, in principle...
Henning Christiansen, Ole Torp Lassen