The 2nd Workshop on Seeking Low-dimensionality in Deep Neural Networks (SLowDNN)

The resurgence of deep neural networks has led to revolutionary success across almost all the areas in engineering and science. However, despite recent endeavors, the underlying principles behind its success still remain a mystery.

This two-day workshop aims to bring together experts in machine learning, applied mathematics, signal processing, and optimization to share recent progress and foster collaborations on mathematical foundations of deep learning. We would like to stimulate vibrate discussions towards bridging the gap between the theory and practice of deep learning by developing a more principled and unified mathematical framework based on the theory and methods for learning low-dimensional models in high-dimensional space.

See the website (link above) for the list of invited speakers.

RSVP for the Zoom link.

Additional Sponsors: National AI Institute for Foundations of Machine Learning, Johns Hopkins Mathematical Institute for Data Science; Michigan Institute for Data Science