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[Moved Online] Hot Topics: Optimal transport and applications to machine learning and statistics May 04, 2020 - May 08, 2020

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May 04, 2020
Monday
09:15 AM - 09:30 AM
  Welcome
David Eisenbud (MSRI - Mathematical Sciences Research Institute)
09:30 AM - 10:30 AM
  Scaling Optimal Transport for High dimensional Learning
Gabriel Peyré (École Normale Supérieure)
10:30 AM - 11:00 AM
  Break
11:00 AM - 12:00 PM
  Linear Unbalanced Optimal Transport
Matthew Thorpe (University of Manchester)
12:00 PM - 02:00 PM
  Break
02:00 PM - 03:00 PM
  Computing Wasserstein barycenters using gradient descent algorithms
Philippe Rigollet (Massachusetts Institute of Technology)
May 05, 2020
Tuesday
09:30 AM - 10:30 AM
  Kalman-Wasserstein Gradient Flows
Franca Hoffman (California Institute of Technology)
10:30 AM - 11:00 AM
  Break
11:00 AM - 12:00 PM
  A Deeper Understanding of the Quadratic Wasserstein Metric in Inverse Data Matching
Yunan Yang (New York University, Courant Institute)
12:00 PM - 02:00 PM
  Break
02:00 PM - 03:00 PM
  A Machine Learning Framework for Solving High-Dimensional Mean Field Game and Mean Field Control Problems
Samy Wu Fung (University of California, Los Angeles)
May 06, 2020
Wednesday
09:30 AM - 10:30 AM
  From quantization of measures to weighted ultrafast diffusion equations
Mikaela Iacobelli (ETH Zurich)
10:30 AM - 11:00 AM
  Break
11:00 AM - 12:00 PM
  Equality of the Jellium and Uniform Electron Gas next-order asymptotic terms for Coulomb and Riesz potentials
Codina Cotar (University College London)
May 07, 2020
Thursday
09:30 AM - 10:30 AM
  Regularity theory and uniform convergence in the large data limit of graph Laplacian eigenvectors on random data clouds.
Nicolas Garcia Trillos (University of Wisconsin-Madison)
10:30 AM - 11:00 AM
  Break
11:00 AM - 12:00 PM
  From an ODE to accelerated stochastic gradient descent: convergence rate and empirical results
Adam Oberman
12:00 PM - 02:00 PM
  Break
02:00 PM - 03:00 PM
  Learning with Few Labeled Data
Pratik Chaudhari (University of Pennsylvania)
03:00 PM - 03:30 PM
  Break
03:30 PM - 04:30 PM
  Fusion with Optimal Transport
Justin Solomon (Massachusetts Institute of Technology)
May 08, 2020
Friday
09:30 AM - 10:30 AM
  Learning with entropy-regularized optimal transport
Aude Genevay (Massachusetts Institute of Technology)
10:30 AM - 11:00 AM
  Break
11:00 AM - 12:00 PM
  Analysis of Gradient Descent on Wide Two-Layer ReLU Neural Networks
Lenaic Chizat (Centre National de la Recherche Scientifique (CNRS))
12:00 PM - 02:00 PM
  Break
02:00 PM - 03:00 PM
  Mean field theory of neural networks: From stochastic gradient descent to Wasserstein gradient flows
Andrea Montanari (Stanford University)
03:00 PM - 03:30 PM
  Break
03:30 PM - 04:30 PM
  Nonlocal-interaction equations on graphs and gradient flows in nonlocal Wasserstein metric
Dejan Slepcev (Carnegie Mellon University)