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APPROX
2005
Springer
111views Algorithms» more  APPROX 2005»
14 years 1 months ago
Sampling Bounds for Stochastic Optimization
A large class of stochastic optimization problems can be modeled as minimizing an objective function f that depends on a choice of a vector x ∈ X, as well as on a random external...
Moses Charikar, Chandra Chekuri, Martin Pál
SIAMCO
2010
169views more  SIAMCO 2010»
13 years 2 months ago
Shape Derivative of Drag Functional
Abstract. In the paper compressible, stationary Navier-Stokes (N-S) equations are considered. The model is well-posed, there exist weak solutions in bounded domains, subject to inh...
Pavel I. Plotnikov, Jan Sokolowski
ICASSP
2008
IEEE
14 years 2 months ago
Sparse reconstruction by separable approximation
Finding sparse approximate solutions to large underdetermined linear systems of equations is a common problem in signal/image processing and statistics. Basis pursuit, the least a...
Stephen J. Wright, Robert D. Nowak, Mário A...
GECCO
2005
Springer
174views Optimization» more  GECCO 2005»
14 years 1 months ago
Emergence of communication in competitive multi-agent systems: a pareto multi-objective approach
In this paper we investigate the emergence of communication in competitive multi-agent systems. A competitive environment is created with two teams of agents competing in an explo...
Michelle McPartland, Stefano Nolfi, Hussein A. Abb...
ECCV
2004
Springer
14 years 9 months ago
A Robust Algorithm for Characterizing Anisotropic Local Structures
This paper proposes a robust estimation and validation framework for characterizing local structures in a positive multi-variate continuous function approximated by a Gaussian-base...
Kazunori Okada, Dorin Comaniciu, Navneet Dalal, Ar...