IFML Seminar
IFML Seminar: 04/03/26 - Learning Mixture Models via Efficient High-dimensional Sparse Fourier Transforms
Abstract: In this work, we give a polynomial time and sample complexity algorithm for efficiently learning the parameters of a mixture of k spherical distributions in d dimensions. Our method succeeds whenever the component...
Upcoming Events
- April32 - 3 pm
IFML Seminar
Event DetailsAbstract: In this work, we give a polynomial time and sample complexity algorithm for efficiently learning the parameters of a...
- 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
- 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...
- October2112:15 - 1 pm
IFML Seminar
Event DetailsRepresentation learning has been widely used in many applications. In this talk, I will present our work which uncovers when...
