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» Analysing Randomized Distributed Algorithms
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NECO
2010
103views more  NECO 2010»
14 years 8 months ago
Posterior Weighted Reinforcement Learning with State Uncertainty
Reinforcement learning models generally assume that a stimulus is presented that allows a learner to unambiguously identify the state of nature, and the reward received is drawn f...
Tobias Larsen, David S. Leslie, Edmund J. Collins,...
STOC
2007
ACM
137views Algorithms» more  STOC 2007»
15 years 10 months ago
Testing k-wise and almost k-wise independence
In this work, we consider the problems of testing whether a distribution over {0, 1}n is k-wise (resp. ( , k)-wise) independent using samples drawn from that distribution. For the...
Noga Alon, Alexandr Andoni, Tali Kaufman, Kevin Ma...
KIVS
2005
Springer
15 years 3 months ago
Measuring Large Overlay Networks - The Overnet Example
Peer-to-peer overlay networks have grown significantly in size and sophistication over the last years. Meanwhile, distributed hash tables (DHT) provide efficient means to create g...
Kendy Kutzner, Thomas Fuhrmann
WWW
2005
ACM
15 years 10 months ago
Sampling search-engine results
We consider the problem of efficiently sampling Web search engine query results. In turn, using a small random sample instead of the full set of results leads to efficient approxi...
Aris Anagnostopoulos, Andrei Z. Broder, David Carm...
MOBIHOC
2005
ACM
15 years 9 months ago
Low-coordination topologies for redundancy in sensor networks
Tiny, low-cost sensor devices are expected to be failure-prone and hence in many realistic deployment scenarios for sensor networks these nodes are deployed in higher than necessa...
Rajagopal Iyengar, Koushik Kar, Suman Banerjee