CS 6784

CS 6784

Course information provided by the Courses of Study 2022-2023.

Extends and complements CS 4780 and CS 5780, giving in-depth coverage of new and advanced methods in machine learning.

When Offered Fall.

Prerequisites/Corequisites Prerequisite: CS 4780 or CS 5780 or equivalents or permission of instructor.

View Enrollment Information

Syllabi: none
  •   Regular Academic Session. 

  • 4 Credits Stdnt Opt

  • Topic: Deep Learning

  • 19106 CS 6784   LEC 001

    • TR Bard Hall 140
    • Aug 22 - Dec 5, 2022
    • Weinberger, K

  • Instruction Mode: In Person
    In this section we will investigate recent trends and developments in deep learning. Students will review recently published papers, give presentations in class, and conduct a significant research project on deep learning.

Syllabi: none
  •   Regular Academic Session. 

  • 4 Credits Stdnt Opt

  • Topic: Machine Learning in Feedback Systems

  • 19107 CS 6784   LEC 002

  • Instruction Mode: In Person
    Feedback between machine learning models and the environment in which they are deployed leads to a host of challenges, from distribution shift to bias to polarization. This graduate level course will introduce theoretical foundations for studying such phenomena. We will cover the frameworks of control theory, reinforcement learning, and online/adaptive learning. Then, we will turn to algorithms for ensuring properties like stability, robustness, safety, and fairness. We will also discuss the social and ethical concerns which motivate these algorithms and properties. Paper discussions and a research project are major parts of the course.