Data Science Finale

Thursday, Dec 13, 2018

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Program:

Foundations of Data Science

Organizers:

David Woodruff (Carnegie Mellon University)

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This one-day meeting will conclude the program on Foundations of Data Science. It will consist of: an open problem session, short talks on research that has come out of the program and recent results of participants and industry visitors, and a session on grand challenges in data science.

Talks

Analysis of a Two-Layer Neural Network via Displacement Convexity

Speaker: Marco Mondelli (Stanford University)

The Degree-d Chow Parameters Problem

Speaker: Ilias Diakonikolas (University of Southern California)

Machine Learning: Dynamics, Economics, and Statistics

Speaker: Michael Jordan (UC Berkeley)

Lower Bounds for Randomized and Parallel Convex Optimization

Speaker: Jelena Diakonikolas (UC Berkeley)

Towards Robust Second-order Training of Neural Networks

Speaker: Amir Gholaminejad (UC Berkeley)

Spectral Sparsification of Simplicial Complexes for Clustering and Label Propagation

Speaker: Bei Wang (University of Utah)