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NIPS
2008
13 years 6 months ago
Fast Rates for Regularized Objectives
We study convergence properties of empirical minimization of a stochastic strongly convex objective, where the stochastic component is linear. We show that the value attained by t...
Karthik Sridharan, Shai Shalev-Shwartz, Nathan Sre...
INFOCOM
2009
IEEE
13 years 11 months ago
Fast Algorithms and Performance Bounds for Sum Rate Maximization in Wireless Networks
Abstract— Sum rate maximization by power control is an important, challenging, and extensively studied problem in wireless networks. It is a nonconvex optimization problem and ac...
Chee-Wei Tan, Mung Chiang, R. Srikant
CORR
2010
Springer
188views Education» more  CORR 2010»
13 years 4 months ago
A unified framework for high-dimensional analysis of $M$-estimators with decomposable regularizers
High-dimensional statistical inference deals with models in which the the number of parameters p is comparable to or larger than the sample size n. Since it is usually impossible ...
Sahand Negahban, Pradeep Ravikumar, Martin J. Wain...
CGO
2004
IEEE
13 years 8 months ago
Exposing Memory Access Regularities Using Object-Relative Memory Profiling
Memory profiling is the process of characterizing a program's memory behavior by observing and recording its response to specific input sets. Relevant aspects of the program&...
Qiang Wu, Artem Pyatakov, Alexey Spiridonov, Easwa...
ICMCS
2006
IEEE
90views Multimedia» more  ICMCS 2006»
13 years 10 months ago
Fast Video Object Selection for Interactive Television
In this paper, we study the problem of the fast selection of video objects, as an aid for the efficient semi-automatic annotation of video programs. In a regular system, the user ...
Rémi Trichet, Bernard Mérialdo