IFML Seminar
IFML Seminar: 03/13/26 - Foundations of Reliable Learning with Imperfect Data
Abstract: A central challenge in machine learning is reliability: ensuring that an algorithm’s predictions remain accurate and stable even when the data is noisy, adversarial, or misspecified. This talk presents recent progress on learning...
Upcoming Events
- March1312:15 - 1:15pm
IFML Seminar
Event DetailsAbstract: A central challenge in machine learning is reliability: ensuring that an algorithm’s predictions remain accurate and stable even when...
- 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
- 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...
- October1412:15 - 1 pm
IFML Seminar
Event DetailsWhen Is Partially Observable Reinforcement Learning Not Scary? Abstract: Partially observability is ubiquitous in applications of Reinforcement Learning (RL…
