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» Approximating max-min linear programs with local algorithms
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NIPS
2003
14 years 11 months ago
On the Concentration of Expectation and Approximate Inference in Layered Networks
We present an analysis of concentration-of-expectation phenomena in layered Bayesian networks that use generalized linear models as the local conditional probabilities. This frame...
XuanLong Nguyen, Michael I. Jordan
STACS
2005
Springer
15 years 3 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
SODA
2012
ACM
297views Algorithms» more  SODA 2012»
13 years 5 days ago
Constant factor approximation algorithm for the knapsack median problem
We give a constant factor approximation algorithm for the following generalization of the k-median problem. We are given a set of clients and facilities in a metric space. Each fa...
Amit Kumar
IPMI
2009
Springer
15 years 4 months ago
Clustering of the Human Skeletal Muscle Fibers Using Linear Programming and Angular Hilbertian Metrics
In this paper, we present a manifold clustering method for the classification of fibers obtained from diffusion tensor images (DTI) of the human skeletal muscle. Using a linear ...
Radhouène Neji, Ahmed Besbes, Nikos Komodak...
SIAMJO
2010
89views more  SIAMJO 2010»
14 years 4 months ago
A New Sequential Optimality Condition for Constrained Optimization and Algorithmic Consequences
Necessary first-order sequential optimality conditions provide adequate theoretical tools to justify stopping criteria for nonlinear programming solvers. These conditions are sati...
Roberto Andreani, José Mario Martíne...