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
- February212:15 - 1 pm
IFML Seminar
Event DetailsAbstract: The Gromov-Wasserstein (GW) distance quantifies dissimilarity between metric measure (mm) spaces and provides a natural correspondence between them…
- January2612:15 - 1 pm
IFML Seminar
Event DetailsAbstract: How can we find and apply the best optimization algorithm for a given problem? This question is as old...
- January262 - 4 pmEvent Details
Connecting undergraduate and graduate students with machine learning research opportunities across campus.
- January25All dayEvent Details
The University of Texas at Austin is creating one of the most powerful artificial intelligence hubs in the academic world...
- January1912:15 - 1 pm
IFML Seminar
Event DetailsAbstract: Parameter-free optimization studies algorithms that adapt to the problem structure at hand. Specifically, such algorithms are capable of converging…
- December812:15 - 1 pm
IFML Seminar
Event DetailsAbstract: The ever-increasing penetration of level-2 autonomous vehicles (AVs) offers an opportunity to reshape the energy efficiency and throughput of...
