February 2021
Challenges in Reliable Machine Learning
Kamalika Chaudhuri (University of California San Diego)
Zoom
ABSTRACT As machine learning is increasingly deployed, there is a need for reliable and robust methods that go beyond simple test accuracy. In this talk, we will discuss two challenges that arise in reliable machine learning. The first is robustness to adversarial examples, which are small imperceptible perturbations to legitimate test inputs that cause machine learning classifiers to misclassify. While recent work has proposed many attacks and defenses, why exactly they arise still remains a mystery. In this talk, we'll…
Find out more »Mobility Forum: Mixed Autonomy Traffic – A Reinforcement Learning Perspective
Cathy Wu (MIT)
online
A weekly seminar series, the MIT Mobility Forum offers an opportunity to showcase the groundbreaking transportation research occurring across the Institute. Faculty members and researchers present their latest findings, ideas, and innovations, followed by a lively discussion. More details can be found at: www.mobilityinitative.mit.edu/mobilityforum Please register at Zoom prior to the seminar.
Find out more »Faster and Simpler Algorithms for List Learning
Jerry Li (Microsoft Research)
Online
Abstract: The goal of list learning is to understand how to learn basic statistics of a dataset when it has been corrupted by an overwhelming fraction of outliers. More formally, one is given a set of points $S$, of which an $\alpha$-fraction $T$ are promised to be well-behaved. The goal is then to output an $O(1 / \alpha)$ sized list of candidate means, so that one of these candidates is close to the true mean of the points in $T$.…
Find out more »Generative Adversarial Training for Gaussian Mixture Models
Farzan Farnia (LIDS)
Zoom
ABSTRACT Generative adversarial networks (GANs) learn the distribution of observed samples through a zero-sum game between two machine players, a generator and a discriminator. While GANs achieve great success in learning the complex distribution of image and text data, they perform suboptimally in learning multi-modal distribution-learning benchmarks including Gaussian mixture models (GMMs). In this talk, we propose Generative Adversarial Training for Gaussian Mixture Models (GAT-GMM), a minimax GAN framework for learning GMMs. Motivated by optimal transport theory, we design the…
Find out more »Mobility Forum: Using data to improve and incentivize safe driving behaviors
Chris Knittel (MIT)
online
A weekly seminar series, the MIT Mobility Forum offers an opportunity to showcase the groundbreaking transportation research occurring across the Institute. Faculty members and researchers present their latest findings, ideas, and innovations, followed by a lively discussion. More details can be found at: www.mobilityinitative.mit.edu/mobilityforum Please register at Zoom prior to the seminar.
Find out more »Structural racism and accountability in the nuclear science community
online
In this seminar, Media Lab researcher and Research to Policy Engagement Fellow Kate Turner and co-authors will lead a discussion on their call for antiracist action and accountability in the US nuclear community.
Find out more »Localization, Uniform Convexity, and Star Aggregation
Suhas Vijaykumar (MIT Sloan)
Zoom
ABSTRACT Offset Rademacher complexities have been shown to imply sharp, data-dependent upper bounds for the square loss in a broad class of problems including improper statistical learning and online learning. We show that in the statistical setting, the offset complexity upper bound can be generalized to any loss satisfying a certain uniform curvature condition; this condition is shown to also capture exponential concavity and self-concordance, uniting several apparently disparate results. By a unified geometric argument, these bounds translate to improper…
Find out more »MIT Sports Summit 2021
online
The MIT Sports Lab invites you to the MIT Sports Summit 2021, a virtual event hosted on Thursday, Feb. 4th and Friday, Feb. 5th! It is an opportunity for the MIT community to interface with the Sports Lab’s affiliates and partners, sharing advances, challenges, and passions at the intersection of engineering and sports. We are featuring talks from leaders in industry and academia, as well as interactive sessions showcasing student research posters and sports tech startups. This is an invitation-only event for current MIT community…
Find out more »LIDS Student Conference
online
The annual LIDS Student Conference is a student-organized, student-run conference that provides an opportunity for graduate students and postdocs to present their research to peers as well as to the community at large.
Find out more »Understanding Cultural Persistence and Change
Nathan Nunn (Harvard University)
Online
Please join us on Tuesday, February 2, 2021 at 3:00pm for the Distinguished Speaker Seminar with Nathan Nunn, Frederic E. Abbe Professor of Economics at Harvard University.
Find out more »