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Poster
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Tue 9:00
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Gradient flow dynamics of shallow ReLU networks for square loss and orthogonal inputs
Etienne Boursier · Loucas PILLAUD-VIVIEN · Nicolas Flammarion
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Poster
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Tue 14:00
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Fast Mixing of Stochastic Gradient Descent with Normalization and Weight Decay
Zhiyuan Li · Tianhao Wang · Dingli Yu
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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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Trajectory Inference via Mean-field Langevin in Path Space
Lénaïc Chizat · Stephen Zhang · Matthieu Heitz · Geoffrey Schiebinger
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Poster
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Thu 9:00
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COLD Decoding: Energy-based Constrained Text Generation with Langevin Dynamics
Lianhui Qin · Sean Welleck · Daniel Khashabi · Yejin Choi
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Poster
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Thu 14:00
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Statistical Learning and Inverse Problems: A Stochastic Gradient Approach
Yuri Fonseca · Yuri Saporito
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Poster
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Thu 14:00
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Benign Underfitting of Stochastic Gradient Descent
Tomer Koren · Roi Livni · Yishay Mansour · Uri Sherman
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Poster
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Wed 9:00
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Generalization Bounds for Stochastic Gradient Descent via Localized ε-Covers
Sejun Park · Umut Simsekli · Murat Erdogdu
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Poster
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Thu 14:00
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Approaching Quartic Convergence Rates for Quasi-Stochastic Approximation with Application to Gradient-Free Optimization
Caio Kalil Lauand · Sean Meyn
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Poster
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Wed 9:00
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Efficiency Ordering of Stochastic Gradient Descent
Jie Hu · Vishwaraj Doshi · Do-Young Eun
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Workshop
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Online Learning of Optimal Control Signals in Stochastic Linear Dynamical Systems
Mohamad Kazem Shirani Faradonbeh
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Poster
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Tue 9:00
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Global Convergence and Stability of Stochastic Gradient Descent
Vivak Patel · Shushu Zhang · Bowen Tian
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