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
- February1612:15 - 1 pm
IFML Seminar
Event DetailsAbstract: Foundational large language models, while successful at shorter contexts, struggle to scale to longer context inputs. Preventing performance decay…
- 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…
