IFML Seminar
IFML Seminar: 04/10/26 - High-Magnetization Sampling at Low Temperatures: Ising Models and Bayesian Sparse Linear Regression
Abstract: Sparse recovery, i.e., estimating a sparse signal theta* in R^d from few noisy measurements y = Xtheta* + xi, is a central problem in high-dimensional statistics. Recent works [KSTZ25, MW26] have taken an...
Upcoming Events
- April1012:15 - 1:15pm
IFML Seminar
Event DetailsAbstract: Sparse recovery, i.e., estimating a sparse signal theta* in R^d from few noisy measurements y = Xtheta* + xi...
- April1712:15 - 1:15pm
IFML Seminar
Event DetailsAbstract: Lengthy data acquisition remains a major bottleneck in magnetic resonance imaging (MRI), often necessitating tradeoffs in resolution and signal-to-…
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...
