
IFML Seminar
IFML Seminar: 04/04/25 - Robust Autonomy Emerges from Self-Play
Abstract: Self-play has powered breakthroughs in two-player and multiplayer games. In this talk, I show that self-play is a surprisingly effective strategy in another domain: robust and naturalistic driving emerges entirely from self-play in...
Upcoming Events
- April412:15 - 1:15pm
IFML Seminar
Abstract: Self-play has powered breakthroughs in two-player and multiplayer games. In this talk, I show that self-play is a surprisingly...
- April1112:15 - 1:15pm
IFML Seminar
Abstract: The widespread deployment of AI systems in critical domains demands more rigorous approaches to evaluating their capabilities and safety...
- April1812:15 - 1:15pm
IFML Seminar
Abstract: Ill-posed inverse problems appear in many critical scientific imaging scenarios where the goal is to reconstruct cleaner images faster...
- April2512:15 - 1:15pm
IFML Seminar
Abstract : In the literature on benign overfitting in linear models, also referred to as minimum norm interpolation, it is...
Past Events
- March313:15 - 4 pm
IFML Seminar
Abstract: Deep learning is delivering unprecedented performance when applied to various data modalities, yet there are data distributions over which...
- March302 - 3 pm
Abstract: Magnetic Resonance Imaging (MRI) enables non-invasive measurement of anatomy with a wide range of image contrast, but incurs significant...
- March2412:15 - 1 pm
IFML Seminar
Abstract: A brain-machine interface (BMII) is a system that enables users to interact with computers and robots through the voluntary...
- March312:15 - 1 pm
IFML Seminar
Abstract: Customer statistics collected in several real-world systems have reflected that users often prefer eliciting their liking for a given...
- February1012:15 - 1 pm
IFML Seminar
Abstract: The activation function deployed in a deep neural network has great influence on the performance of the network at...
- February312:15 - 1 pm
IFML Seminar
Abstract: Graph neural networks (GNNs) are successful at learning representations from most types of network data but suffer from limitations...