Course Overview

This doctoral-level seminar will introduce the statistical and algorithmic principles in the field of scalable machine learning. The course will consist of instructor-led lectures and student-led presentations on current research topics.


This course is intended for PhD students with interest in working on research problems in areas related to scalable machine learning. Students are expected to have a strong background in machine learning at the graduate level (CS260 or equivalent), and also have a solid background in statistics, optimization, and linear algebra. Permission from the instructor is required to enroll. If you think you are qualified for this course, please email Prof. Talwalkar with detailed information about your past training in machine learning (both coursework and research experience).

Grading Policy

Grades will be based on the following components:

Topics and Tentative Schedule

See this google doc.