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» Approximating max-min linear programs with local algorithms
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ICCBR
2003
Springer
15 years 2 months ago
Using Evolution Programs to Learn Local Similarity Measures
Abstract. The definition of similarity measures is one of the most crucial aspects when developing case-based applications. In particular, when employing similarity measures that ...
Armin Stahl, Thomas Gabel
PODC
2005
ACM
15 years 3 months ago
Facility location: distributed approximation
In this paper, we initiate the study of the approximability of the facility location problem in a distributed setting. In particular, we explore a trade-off between the amount of...
Thomas Moscibroda, Roger Wattenhofer
EMNLP
2010
14 years 7 months ago
Turbo Parsers: Dependency Parsing by Approximate Variational Inference
We present a unified view of two state-of-theart non-projective dependency parsers, both approximate: the loopy belief propagation parser of Smith and Eisner (2008) and the relaxe...
André F. T. Martins, Noah A. Smith, Eric P....
DISOPT
2008
138views more  DISOPT 2008»
14 years 9 months ago
An algorithmic framework for convex mixed integer nonlinear programs
This paper is motivated by the fact that mixed integer nonlinear programming is an important and difficult area for which there is a need for developing new methods and software f...
Pierre Bonami, Lorenz T. Biegler, Andrew R. Conn, ...
ICAI
2007
14 years 11 months ago
Dynamic Programming Algorithm for Training Functional Networks
Abstract— The paper proposes a dynamic programming algorithm for training of functional networks. The algorithm considers each node as a state. The problem is formulated as find...
Emad A. El-Sebakhy, Salahadin Mohammed, Moustafa E...