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Poster
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Thu 9:00
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MinMax Methods for Optimal Transport and Beyond: Regularization, Approximation and Numerics
Luca De Gennaro Aquino · Stephan Eckstein
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Poster
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Thu 21:00
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From Boltzmann Machines to Neural Networks and Back Again
Surbhi Goel · Adam Klivans · Frederic Koehler
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Poster
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Tue 9:00
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Zap Q-Learning With Nonlinear Function Approximation
Shuhang Chen · Adithya M Devraj · Fan Lu · Ana Busic · Sean Meyn
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Poster
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Thu 21:00
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Tight last-iterate convergence rates for no-regret learning in multi-player games
Noah Golowich · Sarath Pattathil · Constantinos Daskalakis
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Poster
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Mon 21:00
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Sample Complexity of Asynchronous Q-Learning: Sharper Analysis and Variance Reduction
Gen Li · Yuting Wei · Yuejie Chi · Yuantao Gu · Yuxin Chen
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Workshop
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Fri 12:00
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Extendable and invertible manifold learning with geometry regularized autoencoders
Andres F Duque · Sacha Morin · Guy Wolf · Kevin Moon
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Poster
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Thu 9:00
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Flows for simultaneous manifold learning and density estimation
Johann Brehmer · Kyle Cranmer
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Poster
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Thu 21:00
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Learning Manifold Implicitly via Explicit Heat-Kernel Learning
Yufan Zhou · Changyou Chen · Jinhui Xu
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Workshop
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Accelerating Inverse Design of Nanostructures Using Manifold Learning
Mohammadreza Zandehshahvar · Yashar Kiarashinejad · Muliang Zhu · Hossein Maleki · Omid Hemmatyar · Sajjad Abdollahramezani · Reza Pourabolghasem · Ali Adibi
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Workshop
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Fri 12:00
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Deep Riemannian Manifold Learning
Aaron Lou · Maximilian Nickel · Brandon Amos
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Workshop
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Poster: Solving Compositional Reinforcement Learning Problems via Task Reduction
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Workshop
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Sat 11:30
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Karen E Willcox - Operator Inference: Bridging model reduction and scientific machine learning
Karen Willcox
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