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» Proving Time Bounds for Randomized Distributed Algorithms
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NIPS
2003
14 years 11 months ago
On the Concentration of Expectation and Approximate Inference in Layered Networks
We present an analysis of concentration-of-expectation phenomena in layered Bayesian networks that use generalized linear models as the local conditional probabilities. This frame...
XuanLong Nguyen, Michael I. Jordan
SLS
2009
Springer
243views Algorithms» more  SLS 2009»
15 years 4 months ago
Estimating Bounds on Expected Plateau Size in MAXSAT Problems
Stochastic local search algorithms can now successfully solve MAXSAT problems with thousands of variables or more. A key to this success is how effectively the search can navigate...
Andrew M. Sutton, Adele E. Howe, L. Darrell Whitle...
STOC
1998
ACM
135views Algorithms» more  STOC 1998»
15 years 1 months ago
Checking Polynomial Identities over any Field: Towards a Derandomization?
We present a Monte Carlo algorithm for testing multivariate polynomial identities over any field using fewer random bits than other methods. To test if a polynomial P(x1 ::: xn) ...
Daniel Lewin, Salil P. Vadhan
STOC
2002
ACM
144views Algorithms» more  STOC 2002»
15 years 10 months ago
Improved decremental algorithms for maintaining transitive closure and all-pairs shortest paths
We present improved algorithms for maintaining transitive closure and all-pairs shortest paths/distances in a digraph under deletion of edges. For the problem of transitive closur...
Surender Baswana, Ramesh Hariharan, Sandeep Sen
GECCO
2004
Springer
15 years 3 months ago
A Polynomial Upper Bound for a Mutation-Based Algorithm on the Two-Dimensional Ising Model
Abstract. Fitness functions based on the Ising model are suited excellently for studying the adaption capabilities of randomised search heuristics. The one-dimensional Ising model ...
Simon Fischer