
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
Abstract: 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
Abstract: Retraining a model using its own predictions together with the original, potentially noisy labels is a well-known strategy for...
Past Events
- September2912:15 - 1 pm
IFML Seminar
Abstract: Datasets used in machine learning and statistics are huge and often imperfect, e.g., they contain corrupted data, examples with...
- 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...
- 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...