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» Proving Time Bounds for Randomized Distributed Algorithms
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FOCS
2000
IEEE
15 years 2 months ago
Extracting Randomness from Samplable Distributions
Randomness extractors convert weak sources of randomness into an almost uniform distribution; the conversion uses a small amount of pure randomness. In algorithmic applications, t...
Luca Trevisan, Salil P. Vadhan
INFOCOM
2005
IEEE
15 years 3 months ago
Distributed algorithms for secure multipath routing
— To proactively defend against intruders from readily jeopardizing single-path data sessions, we propose a distributed secure multipath solution to route data across multiple pa...
Patrick P. C. Lee, Vishal Misra, Dan Rubenstein
SIAMDM
2002
124views more  SIAMDM 2002»
14 years 9 months ago
Scheduling Unrelated Machines by Randomized Rounding
We present a new class of randomized approximation algorithms for unrelated parallel machine scheduling problems with the average weighted completion time objective. The key idea i...
Andreas S. Schulz, Martin Skutella
ML
2002
ACM
121views Machine Learning» more  ML 2002»
14 years 9 months ago
Near-Optimal Reinforcement Learning in Polynomial Time
We present new algorithms for reinforcement learning, and prove that they have polynomial bounds on the resources required to achieve near-optimal return in general Markov decisio...
Michael J. Kearns, Satinder P. Singh
RSA
2002
81views more  RSA 2002»
14 years 9 months ago
Decycling numbers of random regular graphs
: The decycling number (G) of a graph G is the smallest number of vertices which can be removed from G so that the resultant graph contains no cycles. In this paper, we study the d...
Sheng Bau, Nicholas C. Wormald, Sanming Zhou