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Analysis of Gradient Descent on Wide Two-Layer ReLU Neural Networks 08-May-2020 11:00 AM PDT - 08-May-2020 12:00 PM PDT
Showing 1 - 18 of 18 matches
Scaling Optimal Transport for High dimensional Learning
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Mean field theory of neural networks: From stochastic gradient descent to Wasserstein gradient flows
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Mean field theory of neural networks: From stochastic gradient descent to Wasserstein gradient flows
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Computing Wasserstein barycenters using gradient descent algorithms
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A Machine Learning Framework for Solving High-Dimensional Mean Field Game and Mean Field Control Problems
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A Machine Learning Framework for Solving High-Dimensional Mean Field Game and Mean Field Control Problems
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Linear Unbalanced Optimal Transport
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Welcome
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Learning with entropy-regularized optimal transport
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Kalman-Wasserstein Gradient Flows
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Fusion with Optimal Transport
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From quantization of measures to weighted ultrafast diffusion equations
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A Deeper Understanding of the Quadratic Wasserstein Metric in Inverse Data Matching
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Learning with Few Labeled Data
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Nonlocal-interaction equations on graphs and gradient flows in nonlocal Wasserstein metric
Date: May 08, 2020
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From an ODE to accelerated stochastic gradient descent: convergence rate and empirical results
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Equality of the Jellium and Uniform Electron Gas next-order asymptotic terms for Coulomb and Riesz potentials
Date: May 06, 2020
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Regularity theory and uniform convergence in the large data limit of graph Laplacian eigenvectors on random data clouds
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