IFML Seminar
IFML Seminar: 10/03/25 - Successor Measures and Self-supervised Reinforcement Learning
Abstract: We introduce a method for learning behavioral foundation models using the successor measure. We show that any visitation distribution can be represented using an affine combination of policy-independent basis functions. By learning these...
Upcoming Events
- October312:15 - 1:15pm
IFML Seminar
Event DetailsAbstract: We introduce a method for learning behavioral foundation models using the successor measure. We show that any visitation distribution...
- October1012:15 - 1:15pm
IFML Seminar
Event DetailsABSTRACT: What would it mean for AI to understand skilled human activity? In augmented reality (AR), a person wearing smart...
- October2412:15 - 1:15pm
IFML Seminar
Event DetailsAbstract: Learning from sequential, temporally-correlated data is a core facet of modern machine learning and statistical modeling. Yet our fundamental...
Past Events
- February113 - 4 pm
ML+ X Seminar
Event DetailsML+X seminar with Joshua Chang, M.D., Ph.D., assistant professor in the Department of Neurology at The University of Texas at...
- December132 - 3 pm
Ethics/Fairness in AI Seminar
Event DetailsChild maltreatment has become a prevalent problem and draws increasing concerns around the world. According to a recent study, approximately...
- November22throughNovember26
Workshop
Event DetailsThe resurgence of deep neural networks has led to revolutionary success across almost all the areas in engineering and science...
- November1912 - 1 pmEvent Details
Abstract: fastMRI is a collaboration project between Facebook AI Research and the NYU School of Medicine with the goal of...
- November123 - 4 pm
ML+ X Seminar
Event DetailsThe recent artificial intelligence (AI) boom has been primarily driven by three confluence forces: algorithms, big-data, and computing power enabled...
- November2throughNovember5
Workshop
Event DetailsMembers of the new NSF AI Institute for Foundations of Machine Learning (IFML) will spend a week in residence at...
