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Tim Tsz-Kit Lau
Tim Tsz-Kit Lau
Other namesTsz Kit Lau
The University of Chicago Booth School of Business
Verified email at chicagobooth.edu - Homepage
Title
Cited by
Cited by
Year
Global Convergence of Block Coordinate Descent in Deep Learning
J Zeng, TTK Lau, S Lin, Y Yao
International Conference on Machine Learning (ICML), 2019
102*2019
A Proximal Block Coordinate Descent Algorithm for Deep Neural Network Training
TTK Lau, J Zeng, B Wu, Y Yao
International Conference on Learning Representations (ICLR) 2018, Workshop Track, 2018
422018
Optimal multivariate Gaussian fitting with applications to PSF modeling in two-photon microscopy imaging
E Chouzenoux, TTK Lau, C Lefort, JC Pesquet
Journal of Mathematical Imaging and Vision 61, 1037-1050, 2019
242019
Bregman Proximal Langevin Monte Carlo via Bregman-Moreau Envelopes
TTK Lau, H Liu
International Conference on Machine Learning (ICML), 12049-12077, 2022
52022
The multi-agent pickup and delivery problem: Mapf, marl and its warehouse applications
TTK Lau, B Sengupta
arXiv preprint arXiv:2203.07092, 2022
42022
Optimal multivariate Gaussian fitting for PSF modeling in two-photon microscopy
TTK Lau, E Chouzenoux, C Lefort, JC Pesquet
Biomedical Imaging (ISBI 2018), 2018 IEEE 15th International Symposium on …, 2018
42018
Accelerated Block Coordinate Proximal Gradients with Applications in High Dimensional Statistics
TK Lau, Y Yao
The 10th NIPS Workshop on Optimization for Machine Learning, NIPS 2017, 2017
32017
Wasserstein Distributionally Robust Optimization with Wasserstein Barycenters
TTK Lau, H Liu
arXiv preprint arXiv:2203.12136, 2022
22022
AdAdaGrad: Adaptive Batch Size Schemes for Adaptive Gradient Methods
TTK Lau, H Liu, M Kolar
arXiv preprint arXiv:2402.11215, 2024
2024
Non-Log-Concave and Nonsmooth Sampling via Langevin Monte Carlo Algorithms
TTK Lau, H Liu, T Pock
arXiv preprint arXiv:2305.15988, 2023
2023
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