Global Convergence of Block Coordinate Descent in Deep Learning J Zeng, TTK Lau, S Lin, Y Yao International Conference on Machine Learning (ICML), 2019 | 107* | 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 | 42 | 2018 |
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 | 26 | 2019 |
Bregman Proximal Langevin Monte Carlo via Bregman-Moreau Envelopes TTK Lau, H Liu International Conference on Machine Learning (ICML), 12049-12077, 2022 | 5 | 2022 |
The multi-agent pickup and delivery problem: Mapf, marl and its warehouse applications TTK Lau, B Sengupta arXiv preprint arXiv:2203.07092, 2022 | 5 | 2022 |
Wasserstein Distributionally Robust Optimization with Wasserstein Barycenters TTK Lau, H Liu arXiv preprint arXiv:2203.12136, 2022 | 4 | 2022 |
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 | 4 | 2018 |
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 | 3 | 2017 |
AdAdaGrad: Adaptive Batch Size Schemes for Adaptive Gradient Methods TTK Lau, H Liu, M Kolar arXiv preprint arXiv:2402.11215, 2024 | 2 | 2024 |
Non-Log-Concave and Nonsmooth Sampling via Langevin Monte Carlo Algorithms TTK Lau, H Liu, T Pock arXiv preprint arXiv:2305.15988, 2023 | 1 | 2023 |
Communication-Efficient Adaptive Batch Size Strategies for Distributed Local Gradient Methods TTK Lau, W Li, C Xu, H Liu, M Kolar arXiv preprint arXiv:2406.13936, 2024 | | 2024 |