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IFML Seminar
Event DetailsAbstract: Foundational large language models, while successful at shorter contexts, struggle to scale to longer context inputs. Preventing performance decay…
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IFML Seminar
Event DetailsAbstract: The Gromov-Wasserstein (GW) distance quantifies dissimilarity between metric measure (mm) spaces and provides a natural correspondence between them…
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IFML Seminar
Event DetailsAbstract: How can we find and apply the best optimization algorithm for a given problem? This question is as old...
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Connecting undergraduate and graduate students with machine learning research opportunities across campus.
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Event Details
The University of Texas at Austin is creating one of the most powerful artificial intelligence hubs in the academic world...
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IFML Seminar
Event DetailsAbstract: Parameter-free optimization studies algorithms that adapt to the problem structure at hand. Specifically, such algorithms are capable of converging…
