
Workshop
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Mathematics of Deep Learning Workshop
2 days of academic research presentations on the mathematical theory underpinning modern machine learning paradigms. Presented by The University of Austin Department of Mathematics, The Machine Learning Lab, and NSF Institute for Foundations of...
Upcoming Events
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February1412:15 - 1:15pm
IFML Seminar
Abstract: Mainstream artificial neural network models, such as Deep Neural Networks (DNNs) are computation-heavy and energy-hungry. Weightless Neural…
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February20throughFebruary21
Workshop
2 days of academic research presentations on the mathematical theory underpinning modern machine learning paradigms. Presented by The University of…
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February2812:15 - 1:15pm
IFML Seminar
Abstract: Learning representations that generalize across diverse downstream tasks is a fundamental challenge in machine learning. Contrastive learning…
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March4throughMarch6
Public Lecture
Join us for the 2025 AI + Robotics Research Symposium -- three days of talks, panels, presentations, and networking opportunities...
Past Events
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September2212:15 - 1 pm
IFML Seminar
Abstract: Graph neural networks (GNNs) are successful at learning representations from most types of network data but suffer from limitations...
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September1512:15 - 1:15pm
IFML Seminar
Abstract: Whittle index policy is a powerful tool to obtain asymptotically optimal solutions for the notoriously intractable problem of restless...
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April2812:15 - 1 pm
IFML Seminar
We discuss the problem of positive-semidefinite extension: extending a partially specified covariance kernel from a subdomain Ω of a rectangular...
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Abstract: We demonstrate the power of combining the forward image acquisition model with deep learning solutions for inverse MRI problems...
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April20throughApril22
Workshop
This workshop aims to bring together researchers with different backgrounds in computer science, machine learning, statistics and math who are...
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April1310 am - 4 pm
The Machine Learning Laboratory Research Symposium will showcase the latest cutting-edge work from our students and faculty. We'll have an...