Bi-Weekly Seminar Series

Seminars are bi-weekly, on Thursdays at 12pm ET (more time zones) and last 90 minutes.

To receive announcements of upcoming seminars, join our mailing list or subscribe to our YouTube. To participate in Zoom, locate the registration link below (posted a few days before the seminar). If you are interested in giving a talk, contact trustworthyml@gmail.com.

FORMAT and instructions

The seminars will take place in Zoom Webinar; some may be recorded and live-streamed to YouTube.

The first hour typically follows one of these formats:

  • 40-min talk, followed by 20-min Q&A and moderated chat on the speaker's journey in ML and research process.

  • Rising Star Spotlights: Two talks of 20-25 mins each, followed by 5-10 min Q&A.

Then after a 5-min break, we reconvene for discussions with fellow participants. Our hope is that this participant-driven discussion in the second hour allows participants to meet new people working in similar research areas. Each seminar will also have a Twitter thread to continue the conversation.

By participating in the seminar, you agree to abide by the Code of Conduct. Please report any issues to trustworthyml@gmail.com.

Joining Zoom: There is a limit of 100 participants in Zoom, first-come-first-serve; registering does not guarantee you a spot. You can join Zoom by clicking the link in your registration confirmation email shortly before the seminar starts. We recommend downloading and installing Zoom in advance.

Live-stream and recording: If Zoom reaches capacity, please watch the YouTube live-stream and check Zoom again in case spots open up. If you do not wish to appear in the live-stream and recording, please only join Zoom in the second hour. You can find recordings of previous seminars here.

Participate: In Zoom, you will be muted in the first hour however you can ask questions using Zoom's Q&A tool. You can also upvote and leave comments on questions. The moderator will select questions, and may call on you to ask yours. In the second hour, you will be un-muted for a free-form discussion with fellow participants. You can use the Twitter thread to continue the conversation after the seminar.

UPCOMING SEMINARS

Click to see abstract, bio, registration link, and Twitter thread. Click here to see the recordings of the past seminars.

Apr 15, 2021: Suresh Venkatasubramanian, University of Utah

The limits of Shapley values as a method for explaining the predictions of an ML system

Abstract: One of the more pressing concerns around the deployment of ML systems is explainability: can we understand why an ML system made the decision that it did. This question can be unpacked in a variety of ways, and one approach that has become popular is the idea of feature influence: that we can assign a score to features that represents their (relative) influence in an outcome (either locally for particular input, or globally). One of the most influential of such approaches has been one based on cooperative game theory, where features are modeled as “players” and feature influence is captured as “player contribution” via the Shapley value of a game. The argument is that the axiomatic framework provided by Shapley values is well-aligned with the needs of an explanation system. But is it? I’ll talk about two pieces of work that nail down mathematical deficiencies of Shapley values as a way of estimating feature influence and quantify the limits of Shapley values via a fascinating geometric interpretation that comes with interesting algorithmic challenges.

Bio: Suresh Venkatasubramanian is a professor at the University of Utah. His background is in algorithms and computational geometry, as well as data mining and machine learning. His current research interests lie in algorithmic fairness, and more generally the impact of automated decision-making systems in society. Suresh was the John and Marva Warnock Assistant Professor at the U, and has received a CAREER award from the NSF for his work in the geometry of probability, as well as a test-of-time award at ICDE 2017 for his work in privacy. His research on algorithmic fairness has received press coverage across North America and Europe, including NPR’s Science Friday, NBC, and CNN, as well as in other media outlets. He is a member of the Computing Community Consortium Council of the CRA, a member of the board of the ACLU in Utah, and a member of New York City’s Failure to Appear Tool (FTA) Research Advisory Council, as well as the Research Advisory Council for the First Judicial District of Pennsylvania.

Zoom registration: https://us02web.zoom.us/webinar/register/WN_FJBqBy7qSS2B_PJbDJEr_A

YouTube live-stream and recording: https://youtu.be/5izWQN3SKQs

Twitter thread to continue the conversation:

Apr 29, 2021 Rising Star Spotlights

Title TBA

Abstract TBA

Zoom registration: Check back again a few days before the seminar.

YouTube live-stream and recording: Check back again a few days before the seminar.

Twitter thread to continue the conversation: Check back again after the seminar.

May 13, 2021: Alexander D'Amour, Google Brain

Title TBA

Abstract TBA

Zoom registration: Check back again a few days before the seminar.

YouTube live-stream and recording: Check back again a few days before the seminar.

Twitter thread to continue the conversation: Check back again after the seminar.

May 27, 2021: Hoda Heidari, Carnegie Mellon University

Title TBA

Abstract TBA

Zoom registration: Check back again a few days before the seminar.

YouTube live-stream and recording: Check back again a few days before the seminar.

Twitter thread to continue the conversation: Check back again after the seminar.

June 10, 2021: Katherine Heller, Google / Duke University

Title TBA

Abstract TBA

Zoom registration: Check back again a few days before the seminar.

YouTube live-stream and recording: Check back again a few days before the seminar.

Twitter thread to continue the conversation: Check back again after the seminar.

June 24, 2021 Rising Star Spotlights

Title TBA

Abstract TBA

Zoom registration: Check back again a few days before the seminar.

YouTube live-stream and recording: Check back again a few days before the seminar.

Twitter thread to continue the conversation: Check back again after the seminar.

July 8, 2021: Cynthia Rudin, Duke University

Title TBA

Abstract TBA

Zoom registration: Check back again a few days before the seminar.

YouTube live-stream and recording: Check back again a few days before the seminar.

Twitter thread to continue the conversation: Check back again after the seminar.

August 19, 2021 Rising Star Spotlights

Title TBA

Abstract TBA

Zoom registration: Check back again a few days before the seminar.

YouTube live-stream and recording: Check back again a few days before the seminar.

Twitter thread to continue the conversation: Check back again after the seminar.

Sep 16, 2021: Sherri Rose, Stanford University

Identifying Subgroups in Algorithmic Fairness

Abstract TBA

Zoom registration: Check back again a few days before the seminar.

YouTube live-stream and recording: Check back again a few days before the seminar.

Twitter thread to continue the conversation: Check back again after the seminar.

Sep 30, 2021: Sanmi Koyejo, University of Illinois at Urbana-Champaign

Title TBA

Abstract TBA

Zoom registration: Check back again a few days before the seminar.

YouTube live-stream and recording: Check back again a few days before the seminar.

Twitter thread to continue the conversation: Check back again after the seminar.

Oct 14, 2021 Rising Star Spotlights

Title TBA

Abstract TBA

Zoom registration: Check back again a few days before the seminar.

YouTube live-stream and recording: Check back again a few days before the seminar.

Twitter thread to continue the conversation: Check back again after the seminar.