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Tim Tsz-Kit Lau

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AdAdaGrad: Adaptive Batch Size Schemes for Adaptive Gradient Methods

Feb 17, 2024
Tim Tsz-Kit Lau, Han Liu, Mladen Kolar

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Non-Log-Concave and Nonsmooth Sampling via Langevin Monte Carlo Algorithms

May 25, 2023
Tim Tsz-Kit Lau, Han Liu, Thomas Pock

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Bregman Proximal Langevin Monte Carlo via Bregman--Moreau Envelopes

Jul 10, 2022
Tim Tsz-Kit Lau, Han Liu

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Wasserstein Distributionally Robust Optimization via Wasserstein Barycenters

Mar 23, 2022
Tim Tsz-Kit Lau, Han Liu

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The Multi-Agent Pickup and Delivery Problem: MAPF, MARL and Its Warehouse Applications

Mar 14, 2022
Tim Tsz-Kit Lau, Biswa Sengupta

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Global Convergence in Deep Learning with Variable Splitting via the Kurdyka-Łojasiewicz Property

Jun 11, 2018
Jinshan Zeng, Shikang Ouyang, Tim Tsz-Kit Lau, Shaobo Lin, Yuan Yao

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A Proximal Block Coordinate Descent Algorithm for Deep Neural Network Training

Mar 24, 2018
Tim Tsz-Kit Lau, Jinshan Zeng, Baoyuan Wu, Yuan Yao

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