- March2412:15 - 1 pm
Abstract: A brain-machine interface (BMII) is a system that enables users to interact with computers and robots through the voluntary...
- March3112:15 - 1 pm
Abstract: Unsupervised learning with functional data is an emerging paradigm of machine learning research with applications to computer vision, climate...
- March313:15 - 4 pm
Abstract: Deep learning is delivering unprecedented performance when applied to various data modalities, yet there are data distributions over which...
This workshop aims to bring together researchers with different backgrounds in computer science, machine learning, statistics and math who are...
- March312:15 - 1 pm
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
Abstract: The activation function deployed in a deep neural network has great influence on the performance of the network at...
- February312:15 - 1 pm
Abstract: Graph neural networks (GNNs) are successful at learning representations from most types of network data but suffer from limitations...
- January2711 am - 12 pm
Co-hosted by UT Good Systems, Forum for Artificial Intelligence, and IFML
- January26All day
The University of Texas at Austin is launching a new online master’s program in AI with the potential to bring...
- January2012 - 1 pm
Abstract: Sparsity has widely shown its versatility in model compression, robustness improvement, and overfitting mitigation by selectively masking out a...