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GECCO
2007
Springer
187views Optimization» more  GECCO 2007»
15 years 4 months ago
Defining implicit objective functions for design problems
In many design tasks it is difficult to explicitly define an objective function. This paper uses machine learning to derive an objective in a feature space based on selected examp...
Sean Hanna
SODA
2010
ACM
163views Algorithms» more  SODA 2010»
15 years 7 months ago
Geometric optimization and sums of algebraic functions
We present a new optimization technique that yields the first FPTAS for several geometric problems. These problems reduce to optimizing a sum of non-negative, constant description...
Antoine Vigneron
PDCN
2004
14 years 11 months ago
Scalable parallel algorithms for difficult combinatorial problems: A case study in optimization
A novel combination of emergent algorithmic methods, powerful computational platforms and supporting infrastructure is described. These complementary tools and technologies are us...
Faisal N. Abu-Khzam, Michael A. Langston, Pushkar ...
ISAAC
1998
Springer
153views Algorithms» more  ISAAC 1998»
15 years 2 months ago
Approximation Algorithms for Some Optimum Communication Spanning Tree Problems
Let G = (V; E; w) be an undirected graph with nonnegative edge length function w and nonnegative vertex weight function r. The optimal product-requirement communication spanning t...
Bang Ye Wu, Kun-Mao Chao, Chuan Yi Tang
SIAMJO
2000
88views more  SIAMJO 2000»
14 years 9 months ago
A Feasible BFGS Interior Point Algorithm for Solving Convex Minimization Problems
Abstract. We propose a BFGS primal-dual interior point method for minimizing a convex function on a convex set defined by equality and inequality constraints. The algorithm generat...
Paul Armand, Jean Charles Gilbert, Sophie Jan-J&ea...