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
- January26All dayEvent Details
The University of Texas at Austin is launching a new online master’s program in AI with the potential to bring...
- January2012 - 1 pm
IFML Seminar
Event DetailsAbstract: Sparsity has widely shown its versatility in model compression, robustness improvement, and overfitting mitigation by selectively masking out a...
- November163 - 5 pmEvent Details
Join us for the 2022 Machine Learning Lab Public Lecture with Alan Bovik!
- November101 - 1:45pm
IFML Seminar
Event DetailsAbstract: This talk will first motivate and illustrate the use of margins as a way to interpret and analyze the...
- November412:15 - 1 pm
IFML Seminar
Event DetailsA central problem in machine learning is as follows: How should we train models using data generated from a collection...
- October2812:15 - 1 pm
IFML Seminar
Event DetailsAbstract: Although Machine learning (ML) algorithms have recently made a huge impact on medical imaging, their development and deployment for...
