Talk
Knowledge Guides for Scalable Machine Learning
Talk by Dr. Anish Arora who is a chairperson of Computer Science and Engineering at The Ohio State University. This talk illustrates a version of Hoare's Law, which says "inside every large (Machine Learned) model there is a small model waiting to get out." Leveraging domain knowledge, we show for problems in classical networking and quantum mechanics how small models can be learned, relative to those learned from black-box methods, with small amounts of data, which still achieving generalizability in not just interpolation but also extrapolation, and also explainability.
- 10 - 10 January,2024
- 04:00 pm - 05:00 pm
- Room 501, Bharti Building