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APPROX
2008
Springer
88views Algorithms» more  APPROX 2008»
13 years 9 months ago
Limitations of Hardness vs. Randomness under Uniform Reductions
We consider (uniform) reductions from computing a function f to the task of distinguishing the output of some pseudorandom generator G from uniform. Impagliazzo and Wigderson [IW]...
Dan Gutfreund, Salil P. Vadhan
TC
1998
13 years 7 months ago
Accuracy vs. Precision in Digital VLSI Architectures for Signal Processing
—The paper provides a sensitivity analysis to measure the loss in accuracy induced by perturbations affecting acyclic computational flows composed of linear convolutions and nonl...
Cesare Alippi, Luciano Briozzo
CVPR
2007
IEEE
14 years 9 months ago
Solving Large Scale Binary Quadratic Problems: Spectral Methods vs. Semidefinite Programming
In this paper we introduce two new methods for solving binary quadratic problems. While spectral relaxation methods have been the workhorse subroutine for a wide variety of comput...
Carl Olsson, Anders P. Eriksson, Fredrik Kahl
ECCV
2002
Springer
14 years 9 months ago
A Tale of Two Classifiers: SNoW vs. SVM in Visual Recognition
Numerous statistical learning methods have been developed for visual recognition tasks. Few attempts, however, have been made to address theoretical issues, and in particular, stud...
Ming-Hsuan Yang, Dan Roth, Narendra Ahuja
GECCO
2007
Springer
184views Optimization» more  GECCO 2007»
14 years 1 months ago
ECGA vs. BOA in discovering stock market trading experts
This paper presents two evolutionary algorithms, ECGA and BOA, applied to constructing stock market trading expertise, which is built on the basis of a set of specific trading ru...
Piotr Lipinski