Presentation Abstract:  Traditional convolutional networks exhibit unprecedented robustness to intraclass nuisances when trained on big data. Generalization with respect to geometric transformations has been achieved via expensive data augmentation. It […]

Presentation Abstract:  The relevant limit for machine learning is not N → infinity but instead N → 0. The human visual system is proof that it is possible to learn […]

Presentation Abstract:  Recently, the transfer learning paradigm has seen a surge of interest due to its impressive capabilities in vision and language. Models are pretrained on ever-growing datasets with enormous […]

Presentation Abstract:  Machine learning systems, in virtually every deployed system, encounter data from a qualitatively different distribution than what they were trained upon.  Effectively dealing with this problem, known as […]

Presentation Abstract: Machine learning has become an indispensable aid to researchers developing the next generation of novel therapeutics. In this talk, I will discuss how some of the most important […]

Presentation Abstract:  The introduction of machine learning (ML) and artificial intelligence (AI) creates unprecedented opportunities for achieving full autonomy. However, learning-based methods in building autonomous systems can be extremely brittle […]