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» Algorithmic randomness of continuous functions
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AE
2005
Springer
14 years 3 months ago
Algorithms (X, sigma, eta): Quasi-random Mutations for Evolution Strategies
Randomization is an efficient tool for global optimization. We here define a method which keeps : – the order 0 of evolutionary algorithms (no gradient) ; – the stochastic as...
Anne Auger, Mohamed Jebalia, Olivier Teytaud
ICGA
1997
134views Optimization» more  ICGA 1997»
13 years 11 months ago
Local Search Genetic Algorithm for Optimization of Highly Reliable Communications Networks
This paper presents a genetic algorithm (GA) with specialized encoding, initialization and local search genetic operators to optimize communication network topologies. This NPhard...
Berna Dengiz, Fulya Altiparmak, Alice E. Smith
FOCS
1989
IEEE
14 years 2 months ago
Constant Depth Circuits, Fourier Transform, and Learnability
In this paper, Boolean functions in ,4C0 are studied using harmonic analysis on the cube. The main result is that an ACO Boolean function has almost all of its “power spectrum”...
Nathan Linial, Yishay Mansour, Noam Nisan
DCC
2003
IEEE
14 years 9 months ago
The Insecurity of the Elliptic Curve Digital Signature Algorithm with Partially Known Nonces
Nguyen and Shparlinski recently presented a polynomial-time algorithm that provably recovers the signer's secret DSA key when a few bits of the random nonces k (used at each s...
Phong Q. Nguyen, Igor Shparlinski
SIGMOD
2004
ACM
153views Database» more  SIGMOD 2004»
14 years 3 months ago
Spatially-decaying aggregation over a network: model and algorithms
Data items are often associated with a location in which they are present or collected, and their relevance or in uence decays with their distance. Aggregate values over such data...
Edith Cohen, Haim Kaplan