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COM S 435: Algorithms for Large Data Sets: Theory and Practice

(Dual-listed with COM S 535). (3-0) Cr. 3.

Prereq: COM S 311 or equivalent; for graduate credit: graduate standing or permission of instructor
Algorithmic challenges involved in solving computational problems on massive data sets. Probabilistic data structures, Curse of Dimensionality and dimensionality reduction, locality sensitive hashing, similarity measures, matrix decompositions. Optimization problems in massive data analysis. Computational problems that arise in the context of web search, social network analysis, online advertising etc. Practical aspects include implementation and performance evaluation of the algorithms on real world data sets. Graduate credit requires a written report on current research.