IFML Seminar
IFML Seminar: 03/13/26 - Foundations of Reliable Learning with Imperfect Data
Abstract: A central challenge in machine learning is reliability: ensuring that an algorithm’s predictions remain accurate and stable even when the data is noisy, adversarial, or misspecified. This talk presents recent progress on learning...
Upcoming Events
- March1312:15 - 1:15pm
IFML Seminar
Event DetailsAbstract: A central challenge in machine learning is reliability: ensuring that an algorithm’s predictions remain accurate and stable even when...
Past Events
- 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…
- September2712:15 - 1 pm
IFML Seminar
Event DetailsAbstract: One of the most natural approaches to reinforcement learning (RL) with function approximation is value iteration, which inductively generates...
