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110
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CORR
2010
Springer
128views Education» more  CORR 2010»
15 years 2 months ago
Sublinear Optimization for Machine Learning
Abstract--We give sublinear-time approximation algorithms for some optimization problems arising in machine learning, such as training linear classifiers and finding minimum enclos...
Kenneth L. Clarkson, Elad Hazan, David P. Woodruff
81
Voted
EUC
2006
Springer
15 years 5 months ago
Optimizing Scheduling Stability for Runtime Data Alignment
Runtime data alignment has been paid attention recently since it can allocate data segment to processors dynamically according to applications' requirement. One of the key opt...
Ching-Hsien Hsu, Chao-Yang Lan, Shih-Chang Chen
SODA
2008
ACM
185views Algorithms» more  SODA 2008»
15 years 3 months ago
Better bounds for online load balancing on unrelated machines
We study the problem of scheduling permanent jobs on unrelated machines when the objective is to minimize the Lp norm of the machine loads. The problem is known as load balancing ...
Ioannis Caragiannis
WCE
2007
15 years 3 months ago
Optimizing Designs based on Risk Approach
— In this paper a new approach to optimize nuclear power plant designs based on global risk reduction are described. In design the focus is on as components quality as redundancy...
Jorge E. Núñez Mc Leod, Selva S. Riv...
111
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APPROX
2008
Springer
107views Algorithms» more  APPROX 2008»
15 years 3 months ago
A General Framework for Designing Approximation Schemes for Combinatorial Optimization Problems with Many Objectives Combined in
Abstract. In this paper, we propose a general framework for designing fully polynomial time approximation schemes for combinatorial optimization problems, in which more than one ob...
Shashi Mittal, Andreas S. Schulz