
IFML Seminar
Large-scale graph machine learning: tradeoffs, guarantees and dynamics
Abstract: Graph neural networks (GNNs) are successful at learning representations from most types of network data but suffer from limitations in large graphs, which do not have the Euclidean structure that time and image...
Upcoming Events
- September2212:15 - 1 pm
IFML Seminar
Abstract: Graph neural networks (GNNs) are successful at learning representations from most types of network data but suffer from limitations...
- October612:15 - 1 pm
IFML Seminar
Abstract: During this presentation, I will delve into an innovative class of optimization problems called finite-sum coupled compositional optimization (FCCO…
Past Events
- April1212 - 1 pm
Abstract Machine learning approaches to medical image reconstruction are of considerable recent interest, especially supervised approaches that use a corpus...
- April712:15 - 1 pm
IFML Seminar
Abstract: Machine learning systems are built using large troves of training data that may contain private or copyrighted content. In...
- 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...
- March3112:15 - 1 pm
IFML Seminar
Abstract: Unsupervised learning with functional data is an emerging paradigm of machine learning research with applications to computer vision, climate...
- 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...