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Poster
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Thu 9:00
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Sobolev Acceleration and Statistical Optimality for Learning Elliptic Equations via Gradient Descent
Yiping Lu · Jose Blanchet · Lexing Ying
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Poster
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Thu 9:00
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Automatic Differentiation of Programs with Discrete Randomness
Gaurav Arya · Moritz Schauer · Frank Schäfer · Christopher Rackauckas
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Poster
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Wed 14:00
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Proximal Point Imitation Learning
Luca Viano · Angeliki Kamoutsi · Gergely Neu · Igor Krawczuk · Volkan Cevher
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Workshop
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Nesterov Meets Optimism: Rate-Optimal Optimistic-Gradient-Based Method for Stochastic Bilinearly-Coupled Minimax Optimization
Chris Junchi Li · Angela Yuan · Gauthier Gidel · Michael Jordan
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Poster
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Thu 14:00
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Recursive Reasoning in Minimax Games: A Level k Gradient Play Method
Zichu Liu · Lacra Pavel
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Workshop
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Quadratic minimization: from conjugate gradients to an adaptive heavy-ball method with Polyak step-sizes
Baptiste Goujaud · Adrien Taylor · Aymeric Dieuleveut
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Poster
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Thu 14:00
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Amortized Proximal Optimization
Juhan Bae · Paul Vicol · Jeff Z. HaoChen · Roger Grosse
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Poster
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Wed 14:00
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Tight Analysis of Extra-gradient and Optimistic Gradient Methods For Nonconvex Minimax Problems
Pouria Mahdavinia · Yuyang Deng · Haochuan Li · Mehrdad Mahdavi
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Workshop
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Stochastic Gradient Descent-Ascent: Unified Theory and New Efficient Methods
Aleksandr Beznosikov · Eduard Gorbunov · Hugo Berard · Nicolas Loizou
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Poster
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Generalization Bounds for Gradient Methods via Discrete and Continuous Prior
Xuanyuan Luo · Bei Luo · Jian Li
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Workshop
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Conditional gradient-based method for bilevel optimization with convex lower-level problem
Ruichen Jiang · Nazanin Abolfazli · Aryan Mokhtari · Erfan Yazdandoost Hamedani
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Poster
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Tue 9:00
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Stability and Generalization for Markov Chain Stochastic Gradient Methods
Puyu Wang · Yunwen Lei · Yiming Ying · Ding-Xuan Zhou
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