Advanced Algorithms
CS/CMS 139
Winter 2016




Tuesday/Thursday 1 - 2:25pm
Annenberg 105

Recitation TBD


Instructor

Thomas Vidick, 207 Annenberg. Office hours Monday 2-3pm, Annenberg 207.

Teaching Assistants

  • Ehsan Abbasi. Office hours TBD.

  • We'll be using piazza for all class-related discussions. Please direct your questions and comments to the course website on piazza.



    Description

    This is an advanced algorithms course specially designed for the CMS Ph.D. program. The course covers advanced topics in the design and analysis of algorithms, emphasizing modern techniques as well as applications in areas of current research interest. Topics covered will include multiplicative weight updates and experts, online learning, semidefinite programming and approximation algorithms, randomized algorithms, concentration bounds and derandomization, spectral methods and analysis of random walks, property testing.

    Prerequisites

    Ma 2, Ma 3, Ma/CS 6a, CS 21, CS 38/138, ACM/EE/CMS 104 and 113, or instructor’s permission.
    This should not be your first course in algorithms. If you have not previously taken undergraduate-level algorithms, please register for CS38 instead.

    Evaluation

    Your grade in the course will be based on a mix of participation, homeworks, course notes scribing, and midterm/final exams. This is a preliminary breakdown that may change during the term, particularly as enrollment levels settle:

    Resources

    We won't be following any particular textbooks. Standard books you may find useful include Randomized Algorithms by Motwani and Raghavan, Approximation Algorithms by Vazirani, The Probabilistic Method by Alon and Spencer.
    Links to similar courses taught at other universities which have lecture notes online:
    See also the following notes available online: