CS 6781

CS 6781

Course information provided by the Courses of Study 2019-2020.

This course will cover fundamental topics in theory of machine earning for modern use, including statistical, computational, and social consideration. We start with a basic statistical and computational toolset required for understanding machine learning. We then explore a number of modern perspectives on machine learning including connections between game theory and machine learning, robustness of machine learning to adversaries, a beyond the worst-case analysis perspective on learning, learning from social and strategic behavior, role of learning in algorithm design, and ethics in machine learning. In addressing these, the course makes connections to statistics, algorithms, complexity theory, optimization, game theory, and more.

Prerequisites/Corequisites Prerequisite: CS 4820 for undergraduate students.

View Enrollment Information

Syllabi: none
  •   Regular Academic Session. 

  • 4 Credits Stdnt Opt

  • 18194 CS 6781   LEC 001

    • TR Bard Hall 140
    • Jan 21 - May 5, 2020
    • Haghtalab, N

  • Instruction Mode: Hybrid - Online & In Person
    Limited to grad students only. All others may add themselves to the waitlist during Add/Drop. Please go to http://www.cs.cornell.edu/courseinfo/enrollment for updates.