MINDS / CIS Seminar Series

Jan
26
Tue
Surya Ganguli
Jan 26 @ 12:00 pm – 1:00 pm

Title- Weaving together machine learning, theoretical physics, and neuroscience

Abstract- An exciting area of intellectual activity in this century may well revolve around a synthesis of machine learning, theoretical physics, and neuroscience. The unification of these fields will likely enable us to exploit the power of complex systems analysis, developed in theoretical physics and applied mathematics, to elucidate the design principles governing neural systems, both biological and artificial, and deploy these principles to develop better algorithms in machine learning. We will give several vignettes in this direction, including: (1) determining the best optimization problem to solve in order to perform regression in high dimensions; (2) finding exact solutions to the dynamics of generalization error in deep linear networks; (3) developing interpretable machine learning to derive and understand state of the art models of the retina; (4) analyzing and explaining the origins of hexagonal firing patterns in recurrent neural networks trained to path-integrate; (5) delineating fundamental theoretical limits on the energy, speed and accuracy with which non-equilibrium sensors can detect signals.

Feb
2
Tue
Wiro Niessen
Feb 2 @ 12:00 pm – 1:00 pm

More information to come soon.

Feb
16
Tue
Andrej Risteski
Feb 16 @ 12:00 pm – 1:00 pm

More information to come soon.

Feb
23
Tue
Mario Sznaier
Feb 23 @ 12:00 pm – 1:00 pm

More information to come soon.

Mar
2
Tue
Lalitha Sankar
Mar 2 @ 12:00 pm – 1:00 pm

More information to come soon.

Mar
9
Tue
Daniela Witten
Mar 9 @ 12:00 pm – 1:00 pm

More information to come soon.

Mar
16
Tue
Smita Krishnaswamy
Mar 16 @ 12:00 pm – 1:00 pm

More information to come soon.

Mar
23
Tue
Rong Ge
Mar 23 @ 12:00 pm – 1:00 pm

More information to come soon.

Mar
30
Tue
Juan Carlos Niebles
Mar 30 @ 12:00 pm – 1:00 pm

More information to come soon.

Apr
6
Tue
Maria De-Arteaga
Apr 6 @ 12:00 pm – 1:00 pm

More information to come soon.