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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
JMLR
2012
13 years 7 months ago
Lifted coordinate descent for learning with trace-norm regularization
We consider the minimization of a smooth loss with trace-norm regularization, which is a natural objective in multi-class and multitask learning. Even though the problem is convex...
Miroslav Dudík, Zaïd Harchaoui, J&eacu...
ICCV
2007
IEEE
16 years 6 months ago
Conditional State Space Models for Discriminative Motion Estimation
We consider the problem of predicting a sequence of real-valued multivariate states from a given measurement sequence. Its typical application in computer vision is the task of mo...
Minyoung Kim, Vladimir Pavlovic
CORR
2008
Springer
113views Education» more  CORR 2008»
15 years 4 months ago
Robustness, Risk, and Regularization in Support Vector Machines
We consider two new formulations for classification problems in the spirit of support vector machines based on robust optimization. Our formulations are designed to build in prote...
Huan Xu, Shie Mannor, Constantine Caramanis
CVPR
2011
IEEE
14 years 8 months ago
Global Optimization for Optimal Generalized Procrustes Analysis
This paper deals with generalized procrustes analysis. This is the problem of registering a set of shape data by estimating a reference shape and a set of rigid transformations gi...
Daniel Pizarro, Adrien Bartoli