IFML Seminar
IFML Seminar: 10/24/25 - Learning from Many Trajectories
Abstract: Learning from sequential, temporally-correlated data is a core facet of modern machine learning and statistical modeling. Yet our fundamental understanding of sequential learning remains incomplete, particularly in the multi-trajectory setting where data consists...
Upcoming Events
- 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...
- November712:15 - 1:15pm
IFML Seminar
Event DetailsAbstract: Retraining a model using its own predictions together with the original, potentially noisy labels is a well-known strategy for...
Past Events
- December45:30 - 8 pm
Public Lecture
Event DetailsPublic event hosted by IBM, the Austin AI Alliance, and the Global AI Alliance (co-founded by IBM). Our Deep Proteins...
- November1512:15 - 1:15pm
IFML Seminar
Event DetailsSpeaker Bio: Zak Mhammedi is a Research Scientist at Google Research , focusing on reinforcement learning and optimization. He completed...
- November13throughNovember15Event Details
Join us for UT Austin’s Year of AI celebration as we showcase the best ideas, innovations and inspiration in the...
- November112:15 - 1 pm
IFML Seminar
Event DetailsSpeaker Bio: Cristopher Moore received his B.A. in Physics, Mathematics, and Integrated Science from Northwestern University, and his Ph.D. in...
- October2512:15 - 1 pm
IFML Seminar
Event DetailsAbstract: Reinforcement learning often faces a trade-off between model flexibility and computational tractability. Flexible models can capture complex…
- October1712:15 - 1 pm
IFML Seminar
Event DetailsAbstract: I will argue that deep networks work well because of a characteristic structure in the space of learnable tasks...
