
IFML Seminar
Large-scale graph machine learning: tradeoffs, guarantees and dynamics
Abstract: Graph neural networks (GNNs) are successful at learning representations from most types of network data but suffer from limitations in large graphs, which do not have the Euclidean structure that time and image...
Upcoming Events
- 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...
- October612:15 - 1 pm
IFML Seminar
Abstract: During this presentation, I will delve into an innovative class of optimization problems called finite-sum coupled compositional optimization (FCCO…
Past Events
- 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...
- 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...
- April20throughApril22
Workshop
This workshop aims to bring together researchers with different backgrounds in computer science, machine learning, statistics and math who are...
- 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...
- April134 - 5 pm
AI Safety Abstract: Thoughts about AI safety, shaped by a year's leave at OpenAI to work on the intersection of...