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ECML
2007
Springer
15 years 5 months ago
Fast Optimization Methods for L1 Regularization: A Comparative Study and Two New Approaches
L1 regularization is effective for feature selection, but the resulting optimization is challenging due to the non-differentiability of the 1-norm. In this paper we compare state...
Mark Schmidt, Glenn Fung, Rómer Rosales
OR
2010
Springer
14 years 6 months ago
A new multi-objective optimization formulation for rail-car fleet sizing problems
Abstract With potential application to a variety of industries, fleet sizing problems present a prevalent and significant challenge for engineers and managers. This is especially t...
Hamid Reza Sayarshad, Timothy Marler
CORR
2010
Springer
146views Education» more  CORR 2010»
14 years 11 months ago
Adaptive Submodularity: A New Approach to Active Learning and Stochastic Optimization
Solving stochastic optimization problems under partial observability, where one needs to adaptively make decisions with uncertain outcomes, is a fundamental but notoriously diffic...
Daniel Golovin, Andreas Krause
PDP
2008
IEEE
15 years 6 months ago
Internet-Scale Simulations of a Peer Selection Algorithm
The match between a peer-to-peer overlay and the physical Internet infrastructure is a constant issue. Time-constrained peer-to-peer applications such as live streaming systems ar...
Ali Boudani, Yiping Chen, Gilles Straub, Gwendal S...
IPPS
1999
IEEE
15 years 4 months ago
Reducing I/O Complexity by Simulating Coarse Grained Parallel Algorithms
Block-wise access to data is a central theme in the design of efficient external memory (EM) algorithms. A second important issue, when more than one disk is present, is fully par...
Frank K. H. A. Dehne, David A. Hutchinson, Anil Ma...