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(Complete Item Description)
- Abstract:
This course is a first-year graduate course in algorithms. Emphasis is placed on fundamental algorithms and advanced methods of algorithmic design, analysis, and implementation. Techniques to be covered include amortization, randomization, fingerprinting, word-level parallelism, bit scaling, dynamic programming, network flow, linear programming, fixed-parameter algorithms, and approximation algorithms. Domains include string algorithms, network optimization, parallel algorithms, computational geometry, online algorithms, external memory, cache, and streaming algorithms, and data structures.
- Subject:
- Science and Technology
- Grade Level:
- Post-secondary
- Collection:
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MIT OpenCourseWare
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(Complete Item Description)
- Abstract:
Thorough treatment of linear programming and combinatorial optimization. Topics include network flow, matching theory, matroid optimization, and approximation algorithms for NP-hard problems. 18.310 helpful but not required.
- Subject:
- Mathematics and Statistics
- Grade Level:
- Post-secondary
- Collection:
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MIT OpenCourseWare
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(Complete Item Description)
- Abstract:
This is a new class on the topic of field (that is, 'in situ') and laboratory experiments in the social sciences - both what these experiments have taught and can teach us and how to conduct them.
- Subject:
- Social Sciences
- Grade Level:
- Post-secondary
- Collection:
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MIT OpenCourseWare
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(Complete Item Description)
- Abstract:
Studies how randomization can be used to make algorithms simpler and more efficient via random sampling, random selection of witnesses, symmetry breaking, and Markov chains. Models of randomized computation. Data structures: hash tables, and skip lists. Graph algorithms: minimum spanning trees, shortest paths, and minimum cuts. Geometric algorithms: convex hulls, linear programming in fixed or arbitrary dimension. Approximate counting; parallel algorithms; online algorithms; derandomization techniques; and tools for probabilistic analysis of algorithms.
- Subject:
- Science and Technology
- Grade Level:
- Post-secondary
- Collection:
-
MIT OpenCourseWare