ASSET Seminar: New approaches to detecting and adapting to domain shifts in machine learning, Zico Kolter, Ph.D. (Carnegie Mellon University)
ABSTRACT: Machine learning systems, in virtually every deployed system, encounter data from a qualitatively different distribution than what they were trained upon. Effectively dealing with this problem, known as domain […]
ASSET Seminar: What Transfers in Transfer Learning?, Eric Wong (University of Pennsylvania)
Abstract: Recently, the transfer learning paradigm has seen a surge of interest due to its impressive capabilities in vision and language. Models are pretrained on ever-growing datasets with enormous parameter […]
ASSET Seminar: Learning with Small Data, Pratik Chaudhari (University of Pennsylvania)
Abstract: The relevant limit for machine learning is not N → infinity but instead N → 0. The human visual system is proof that it is possible to learn categories […]
ASSET Seminar: Equivariance in Deep Learning, Kostas Daniilidis (University of Pennsylvania)
ABSTRACT Traditional convolutional networks exhibit unprecedented robustness to intraclass nuisances when trained on big data. Generalization with respect to geometric transformations has been achieved via expensive data augmentation. It has been shown recently that […]
ASSET Seminar: Explainable AI via Semantic Information Pursuit (René Vidal, Johns Hopkins University)
Presentation Abstract: There is a significant interest in developing ML algorithms whose final predictions can be explained in domain-specific terms that are understandable to a human. Providing such an “explanation” […]
ASSET Seminar: When Will You Become the Best Reviewer of Your Own Papers? A Truthful Owner-Assisted Scoring Mechanism (Weijie Su, University of Pennsylvania)
Presentation Abstract: Alice submits a number of papers to a machine learning conference and has knowledge of the quality of her papers. Given noisy grades provided by independent reviewers, can […]
PRECISE Seminar: Investigate and Mitigate the Attacks Caused by Out-of-Band Signals
Abstract Sensing and actuation systems are entrusted with increasing intelligence to perceive the environment and react to it. Their reliability often relies on the trustworthiness of sensors. As process automation […]
ASSET Seminar: Robust and Equitable Uncertainty Estimation (Aaron Roth, University of Pennsylvania)
Presentation Abstract: Machine learning provides us with an amazing set of tools to make predictions, but how much should we trust particular predictions? To answer this, we need a way […]
BE Doctoral Dissertation Defense: “Machine learning as tool and theory for computational neuroscience” (Ari Benjamin)
The Department of Bioengineering at the University of Pennsylvania and Dr. Konrad Kording are pleased to announce the Doctoral Dissertation Defense of Ari Benjamin. Title “Machine learning as tool and theory […]
Layer by Atomic Layer – MOCVD Growth for a Carbon Neutral Society: A Symposium to honor Dr. Russell Dupuis and Dr. Daniel Dapkus, recipients of the 2022 Benjamin Franklin Medal in Electrical Engineering
The School of Engineering and Applied Science is honored to co-sponsor, with Drexel University and the Franklin Institute, a symposium to honor the recipients of the 2022 Benjamin Franklin Medal […]