The adaptive mesh refinement algorithm technique, shown above, is used to break complex computing problems into smaller pieces. (Image courtesy of Ernest Orlando Lawrence Berkeley National Laboratory.)
Instructor(s)
Prof. David R. Karger
MIT Course Number
6.854J / 18.415J
As Taught In
Fall 2005
Level
Graduate
Course Description
Course Features
Course Description
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.
Other Versions
Other OCW Versions
OCW has published multiple versions of this subject. 