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
- September1912:15 - 1:15pm
IFML Seminar
Event DetailsAbstract: LLMs have not only revolutionized text-based natural language processing, but their multimodal extensions have proven to be extremely powerful...
- September1212:15 - 1:15pm
IFML Seminar
Event DetailsAbstract: A fundamental problem in optimization is finding an ε-first-order stationary point of a smooth function using only gradient information...
- July29All dayEvent Details
AUSTIN, Texas — A National Science Foundation artificial intelligence institute based at The University of Texas at Austin will receive...
- May212:15 - 1:15pm
IFML Seminar
Event DetailsAbstract: We revisit the fundamental problem of learning with distribution shift, where a learner is given labeled samples from training...
- April2512:15 - 1:15pm
IFML Seminar
Event DetailsAbstract : In the literature on benign overfitting in linear models, also referred to as minimum norm interpolation, it is...
- April1812:15 - 1:15pm
IFML Seminar
Event DetailsAbstract: Ill-posed inverse problems appear in many critical scientific imaging scenarios where the goal is to reconstruct cleaner images faster...
