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CORR
2004
Springer
103views Education» more  CORR 2004»
15 years 5 months ago
Online convex optimization in the bandit setting: gradient descent without a gradient
We study a general online convex optimization problem. We have a convex set S and an unknown sequence of cost functions c1, c2, . . . , and in each period, we choose a feasible po...
Abraham Flaxman, Adam Tauman Kalai, H. Brendan McM...
TIT
2008
105views more  TIT 2008»
15 years 4 months ago
State Discrimination With Post-Measurement Information
We introduce a new state discrimination problem in which we are given additional information about the state after the measurement, or more generally, after a quantum memory bound ...
Manuel A. Ballester, Stephanie Wehner, Andreas Win...
TNN
2010
234views Management» more  TNN 2010»
15 years 19 days ago
Novel maximum-margin training algorithms for supervised neural networks
This paper proposes three novel training methods, two of them based on the back-propagation approach and a third one based on information theory for Multilayer Perceptron (MLP) bin...
Oswaldo Ludwig, Urbano Nunes
CVPR
2009
IEEE
17 years 1 months ago
A Revisit of Generative Model for Automatic Image Annotation using Markov Random Fields
Much research effort on Automatic Image Annotation (AIA) has been focused on Generative Model, due to its well formed theory and competitive performance as compared with many we...
Yu Xiang (Fudan University), Xiangdong Zhou (Fudan...
ICML
2007
IEEE
16 years 6 months ago
Pegasos: Primal Estimated sub-GrAdient SOlver for SVM
We describe and analyze a simple and effective iterative algorithm for solving the optimization problem cast by Support Vector Machines (SVM). Our method alternates between stocha...
Shai Shalev-Shwartz, Yoram Singer, Nathan Srebro