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Randomized algorithm

Known as: Derandomization, Probabilistic computational complexity, Probabilistic-Complexity Theory 
A randomized algorithm is an algorithm that employs a degree of randomness as part of its logic. The algorithm typically uses uniformly random bits… Expand
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Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Review
2011
Review
2011
Randomized algorithms for very large matrix problems have received a great deal of attention in recent years. Much of this work… Expand
Highly Cited
2009
Highly Cited
2009
This paper presents interactive image editing tools using a new randomized algorithm for quickly finding approximate nearest… Expand
Highly Cited
2009
Highly Cited
2009
This paper presents interactive image editing tools using a new randomized algorithm for quickly finding approximate nearest… Expand
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Highly Cited
2006
Highly Cited
2006
Motivated by applications to sensor, peer-to-peer, and ad hoc networks, we study distributed algorithms, also known as gossip… Expand
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Highly Cited
2006
Highly Cited
2006
Randomized algorithms (making random choices during their execution) play an important role in modern computer science, with… Expand
Highly Cited
2005
Highly Cited
2005
Preface 1. Events and probability 2. Discrete random variables and expectation 3. Moments and deviations 4. Chernoff bounds 5… Expand
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Highly Cited
2000
Highly Cited
2000
We have already seen some uses of randomization in the design of on line algorithms In these notes we shall describe other… Expand
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Highly Cited
1996
Highly Cited
1996
Randomized algorithms, once viewed as a tool in computational number theory, have by now found widespread application. Growth has… Expand
Highly Cited
1995
Highly Cited
1995
For many applications, a randomized algorithm is either the simplest or the fastest algorithm available, and sometimes both. This… Expand
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Highly Cited
1987
Highly Cited
1987
We present randomized algorithms to solve the following string-matching problem and some of its generalizations: Given a string X… Expand