Overview

This is a graduate-level reading seminar on application of machine learning in computer systems. In this course we will explore the state of the art in how machine learning is being used in systems, why, and where there are opportunities for further advancement. The objectives of this course are-

The course is structured around lectures by instructor (Saurabh Agarwal), guest lectures and paper readings by students.

The course heavily borrows its format from Prof. Aditya Akella’s previous iteration.

Topics

Contact and Office Hours

Post question on Ed.

Office hours 11 AM - Noon every Thursday.

Email - saurabh.agarwal at utexas.edu

Course Organization

Paper Reviews

You are required to read and submit a response to the canvas assignment Ed discussion posted for each assigned paper reading. The Paper reviews our due at 9 AM 6PM before each class on Ed.

In class Discussion

During the class we will discuss additional instructor provided discussion points related to the paper. You are required to submit your summary of discussion points by 9PM the day of class.

Presentations and Leading Class Discussions

Each paper will be assigned with one leader. The leader is supposed to present the paper, including going into the relevant background. Post presentation the leader is also responsible for running the discussion session with the aid of instructor. You are supposed present twice during the semester. Please sign up for the schedule here. The slides for the presentation are due at 9 AM the day before the class. Please email the slides to the instructor.

Research Project

The course project is an open-ended research project, done in groups of two or three. A list of project ideas will be posted in Canvas. You are required to submit a proposal and a final report. There will be a in-class final presentation.

Grading