IFML Seminar
IFML Seminar: 04/03/26 - Learning Mixture Models via Efficient High-dimensional Sparse Fourier Transforms
Abstract: In this work, we give a polynomial time and sample complexity algorithm for efficiently learning the parameters of a mixture of k spherical distributions in d dimensions. Our method succeeds whenever the component...
Upcoming Events
- April32 - 3 pm
IFML Seminar
Event DetailsAbstract: In this work, we give a polynomial time and sample complexity algorithm for efficiently learning the parameters of a...
- April1712:15 - 1:15pm
IFML Seminar
Event DetailsAbstract: Lengthy data acquisition remains a major bottleneck in magnetic resonance imaging (MRI), often necessitating tradeoffs in resolution and signal-to-…
Past Events
- 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...
- September1312:15 - 1 pm
IFML Seminar
Event DetailsAbstract: We consider the problem of model selection in a high-dimensional sparse linear regression model under privacy constraints. We propose...
- September612:15 - 1 pm
IFML Seminar
Event DetailsAbstract: From the moment we open our eyes, we are surrounded by people. By observing the people around us, we...
- August2312:15 - 1 pm
IFML Seminar
Event DetailsAbstract: Distribution shifts, where deployment conditions differ from the training environment, are pervasive in real-world AI applications and often…
- August5All dayEvent Details
IFML Director Adam Klivans and IFML Co-director Alex Dimakis discuss DataComp , UT Austin's new Center for Generative AI, and...
- July21throughJuly26Event Details
IFML has partnered with UT Computer Science Summer Academies to launch the Academy for Machine Learning
