IFML Seminar
IFML Seminar: 05/02/25 - A New Paradigm for Learning with Distribution Shift
Abstract: We revisit the fundamental problem of learning with distribution shift, where a learner is given labeled samples from training distribution D, unlabeled samples from test distribution D′ and is asked to output a...
Upcoming Events
- 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...
Past Events
- 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...
- October412:15 - 1 pm
IFML Seminar
Event DetailsAbstract: Sequential decision-making (SDM) is crucial for adapting machine learning to dynamic real-world scenarios such as fluctuating markets or evolving…
