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.

Prerequisites

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.

Piazza Forum

We will use Piazza for class discussions. Please go to this Piazza website to join the course forum (note: you must use a ucla.edu email account to join the forum). Students are strongly encouraged to post on this forum rather than emailing Prof. Talwalkar directly. Students should use Piazza to:

Also, please be polite.

Grading Policy

Grades will be based on the following components:

Tentative Topics and Schedule

See this google doc.