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Invited Paper Session

Dynamics of High-Dimensional Statistical Learning

Mon, Aug 5, 8:30 AM - 10:20 AM

Zhou FanChair

IMS

4 Presentations

Feature Learning and Margin Maximization via Mirror Descent

8:35 AM - 9:00 AM

Matus Telgarsky (New York University)

High Dimensional Dynamics of Gradient Descent in the Multi-spike Matrix and Tensor PCA Problem

9:00 AM - 9:25 AM

Cedric Gerbelot (Courant Institute, New York University)

Hitting the High-D(imensional) Notes: An ODE for SGD learning dynamics via homogenization

9:25 AM - 9:50 AM

Courtney Paquette (McGill University)

Quantum Approximate Optimization Algorithm: Can It Bridge the Statistical-Computational Gap in Random Combinatorial Optimization?

9:50 AM - 10:15 AM

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