Tim Tsz-Kit Lau

16 papers A* 2Journal 11Unranked 3

Year	Rank	Type	Title / Venue / Authors
2025	—	`conf`	Adaptive Batch Size Schedules for Distributed Training of Language Models with Data and Model Parallelism. CPAL Tim Tsz-Kit Lau, Weijian Li, Chenwei Xu, Han Liu, Mladen Kolar
2025	J	`jnl`	PolarGrad: A Class of Matrix-Gradient Optimizers from a Unifying Preconditioning Perspective. CoRR Tim Tsz-Kit Lau, Qi Long, Weijie Su
2024	J	`jnl`	AdAdaGrad: Adaptive Batch Size Schemes for Adaptive Gradient Methods. CoRR Tim Tsz-Kit Lau, Han Liu, Mladen Kolar
2024	J	`jnl`	Adaptive Batch Size Schedules for Distributed Training of Language Models with Data and Model Parallelism. CoRR Tim Tsz-Kit Lau, Weijian Li, Chenwei Xu, Han Liu, Mladen Kolar
2024	J	`jnl`	Communication-Efficient Adaptive Batch Size Strategies for Distributed Local Gradient Methods. CoRR Tim Tsz-Kit Lau, Weijian Li, Chenwei Xu, Han Liu, Mladen Kolar
2023	J	`jnl`	Non-Log-Concave and Nonsmooth Sampling via Langevin Monte Carlo Algorithms. CoRR Tim Tsz-Kit Lau, Han Liu, Thomas Pock
2022	A*	`conf`	Bregman Proximal Langevin Monte Carlo via Bregman-Moreau Envelopes. ICML Tim Tsz-Kit Lau, Han Liu
2022	J	`jnl`	Bregman Proximal Langevin Monte Carlo via Bregman-Moreau Envelopes. CoRR Tim Tsz-Kit Lau, Han Liu
2022	J	`jnl`	The Multi-Agent Pickup and Delivery Problem: MAPF, MARL and Its Warehouse Applications. CoRR Tim Tsz-Kit Lau, Biswa Sengupta
2022	J	`jnl`	Wasserstein Distributionally Robust Optimization via Wasserstein Barycenters. CoRR Tim Tsz-Kit Lau, Han Liu
2019	A*	`conf`	Global Convergence of Block Coordinate Descent in Deep Learning. ICML Jinshan Zeng, Tim Tsz-Kit Lau, Shaobo Lin, Yuan Yao
2019	J	`jnl`	Optimal Multivariate Gaussian Fitting with Applications to PSF Modeling in Two-Photon Microscopy Imaging. J. Math. Imaging Vis. Emilie Chouzenoux, Tim Tsz-Kit Lau, Claire Lefort, Jean-Christophe Pesquet
2018	—	`conf`	A Proximal Block Coordinate Descent Algorithm for Deep Neural Network Training. ICLR (Workshop) Tim Tsz-Kit Lau, Jinshan Zeng, Baoyuan Wu, Yuan Yao
2018	J	`jnl`	A Proximal Block Coordinate Descent Algorithm for Deep Neural Network Training. CoRR Tim Tsz-Kit Lau, Jinshan Zeng, Baoyuan Wu, Yuan Yao
2018	J	`jnl`	Block Coordinate Descent for Deep Learning: Unified Convergence Guarantees. CoRR Jinshan Zeng, Tim Tsz-Kit Lau, Shaobo Lin, Yuan Yao
2018	—	`conf`	Optimal multivariate Gaussian fitting for PSF modeling in two-photon microscopy. ISBI Tim Tsz-Kit Lau, Emilie Chouzenoux, Claire Lefort, Jean-Christophe Pesquet