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» Optimal 3-terminal cuts and linear programming
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KDD
2009
ACM
188views Data Mining» more  KDD 2009»
14 years 6 months ago
Mining discrete patterns via binary matrix factorization
Mining discrete patterns in binary data is important for subsampling, compression, and clustering. We consider rankone binary matrix approximations that identify the dominant patt...
Bao-Hong Shen, Shuiwang Ji, Jieping Ye
ORL
2006
105views more  ORL 2006»
13 years 6 months ago
Inventory placement in acyclic supply chain networks
The strategic safety stock placement problem is a constrained separable concave minimization problem and so is solvable, in principle, as a sequence of mixed-integer programming p...
Thomas L. Magnanti, Zuo-Jun Max Shen, Jia Shu, Dav...
4OR
2010
137views more  4OR 2010»
13 years 6 months ago
Extended formulations in combinatorial optimization
This survey is concerned with the size of perfect formulations for combinatorial optimization problems. By "perfect formulation", we mean a system of linear inequalities...
Michele Conforti, Gérard Cornuéjols,...
STACS
2005
Springer
13 years 11 months ago
Sampling Sub-problems of Heterogeneous Max-cut Problems and Approximation Algorithms
Abstract Abstract. Recent work in the analysis of randomized approximation algorithms for NP-hard optimization problems has involved approximating the solution to a problem by the ...
Petros Drineas, Ravi Kannan, Michael W. Mahoney
NIPS
2008
13 years 7 months ago
An Extended Level Method for Efficient Multiple Kernel Learning
We consider the problem of multiple kernel learning (MKL), which can be formulated as a convex-concave problem. In the past, two efficient methods, i.e., Semi-Infinite Linear Prog...
Zenglin Xu, Rong Jin, Irwin King, Michael R. Lyu