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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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Tue 9:00
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Unifying and Boosting Gradient-Based Training-Free Neural Architecture Search
YAO SHU · Zhongxiang Dai · Zhaoxuan Wu · Bryan Kian Hsiang Low
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Poster
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Wed 9:00
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Gradient-Free Methods for Deterministic and Stochastic Nonsmooth Nonconvex Optimization
Tianyi Lin · Zeyu Zheng · Michael Jordan
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Poster
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Tue 14:00
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Frank-Wolfe-based Algorithms for Approximating Tyler's M-estimator
Lior Danon · Dan Garber
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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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Tue 14:00
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A Projection-free Algorithm for Constrained Stochastic Multi-level Composition Optimization
Tesi Xiao · Krishnakumar Balasubramanian · Saeed Ghadimi
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Panel
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Tue 10:15
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Panel 1A-3: A gradient sampling… & Local Bayesian optimization…
Swati Padmanabhan · Quan Nguyen
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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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Thu 14:00
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Optimal Comparator Adaptive Online Learning with Switching Cost
Zhiyu Zhang · Ashok Cutkosky · Yannis Paschalidis
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Workshop
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Parameter Free Dual Averaging: Optimizing Lipschitz Functions in a Single Pass
Aaron Defazio · Konstantin Mishchenko
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Poster
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Tue 14:00
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Fast Stochastic Composite Minimization and an Accelerated Frank-Wolfe Algorithm under Parallelization
Benjamin Dubois-Taine · Francis Bach · Quentin Berthet · Adrien Taylor
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Workshop
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Near-Optimal Deployment Efficiency in Reward-Free Reinforcement Learning with Linear Function Approximation
Dan Qiao · Yu-Xiang Wang
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