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File: 6-856j-fall-2002.zip
This OER is part of OCW: Randomized Algorithms
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Inherited Tag(s):
- electrical engineering and computer science
- randomized algorithms
- algorithms
- efficient in time and space
- randomization
- computational problems
- data structures
- graph algorithms
- optimization
- geometry
- markov chains
- sampling
- estimation
- geometric algorithms
- parallel and distributed algorithms
- parallel and ditributed algorithm
- parallel and distributed algorithm
- random sampli
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Description:This course examines how randomization can be used to make algorithms simpler and more efficient via random sampling, random selection of witnesses, symmetry breaking, and Markov chains. Topics covered include: randomized computation; data structures (hash tables, skip lists); graph algorithms (minimum spanning trees, shortest paths, minimu
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Description:This course examines how randomization can be used to make algorithms simpler and more efficient via random sampling, random selection of witnesses, symmetry breaking, and Markov chains. Topics covered include: randomized computation; data structures (hash tables, skip lists); graph algorithms (minimum spanning trees, shortest paths, minimu
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Description:This course examines how randomization can be used to make algorithms simpler and more efficient via random sampling, random selection of witnesses, symmetry breaking, and Markov chains. Topics covered include: randomized computation; data structures (hash tables, skip lists); graph algorithms (minimum spanning trees, shortest paths, minimu
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