Toh, Kim-Chuan

20 publications

TMLR 2025 Adam-Family Methods with Decoupled Weight Decay in Deep Learning Kuangyu Ding, Nachuan Xiao, Kim-chuan Toh

NeurIPS 2025 GRIFFIN: Effective Token Alignment for Faster Speculative Decoding Shijing Hu, Jingyang Li, Xingyu Xie, Zhihui Lu, Kim-chuan Toh, Pan Zhou

ICCV 2025 Memory-Efficient 4-Bit Preconditioned Stochastic Optimization Jingyang Li, Kuangyu Ding, Kim-Chuan Toh, Pan Zhou

JMLR 2025 Nonconvex Stochastic Bregman Proximal Gradient Method with Application to Deep Learning Kuangyu Ding, Jingyang Li, Kim-Chuan Toh

ICLR 2025 Towards Understanding Why FixMatch Generalizes Better than Supervised Learning Jingyang Li, Jiachun Pan, Vincent Y. F. Tan, Kim-chuan Toh, Pan Zhou

JMLR 2024 Accelerating Nuclear-Norm Regularized Low-Rank Matrix Optimization Through Burer-Monteiro Decomposition Ching-pei Lee, Ling Liang, Tianyun Tang, Kim-Chuan Toh

JMLR 2024 Adam-Family Methods for Nonsmooth Optimization with Convergence Guarantees Nachuan Xiao, Xiaoyin Hu, Xin Liu, Kim-Chuan Toh

JMLR 2024 Estimation of Sparse Gaussian Graphical Models with Hidden Clustering Structure Meixia Lin, Defeng Sun, Kim-Chuan Toh, Chengjing Wang

JMLR 2024 On Efficient and Scalable Computation of the Nonparametric Maximum Likelihood Estimator in Mixture Models Yangjing Zhang, Ying Cui, Bodhisattva Sen, Kim-Chuan Toh

AAAI 2024 On Partial Optimal Transport: Revising the Infeasibility of Sinkhorn and Efficient Gradient Methods Anh Duc Nguyen, Tuan Dung Nguyen, Quang Minh Nguyen, Hoang H. Nguyen, Lam M. Nguyen, Kim-Chuan Toh

JMLR 2024 Win: Weight-Decay-Integrated Nesterov Acceleration for Faster Network Training Pan Zhou, Xingyu Xie, Zhouchen Lin, Kim-Chuan Toh, Shuicheng Yan

NeurIPSW 2022 Dimension-Reduced Adaptive Gradient Method Jingyang Li, Pan Zhou, Kuangyu Ding, Kim-Chuan Toh, Yinyu Ye

JMLR 2022 On Regularized Square-Root Regression Problems: Distributionally Robust Interpretation and Fast Computations Hong T.M. Chu, Kim-Chuan Toh, Yangjing Zhang

JMLR 2021 A Fast Globally Linearly Convergent Algorithm for the Computation of Wasserstein Barycenters Lei Yang, Jia Li, Defeng Sun, Kim-Chuan Toh

JMLR 2021 Convex Clustering: Model, Theoretical Guarantee and Efficient Algorithm Defeng Sun, Kim-Chuan Toh, Yancheng Yuan

JMLR 2020 A Sparse Semismooth Newton Based Proximal Majorization-Minimization Algorithm for Nonconvex Square-Root-Loss Regression Problems Peipei Tang, Chengjing Wang, Defeng Sun, Kim-Chuan Toh

JMLR 2019 Solving the OSCAR and SLOPE Models Using a Semismooth Newton-Based Augmented Lagrangian Method Ziyan Luo, Defeng Sun, Kim-Chuan Toh, Naihua Xiu

ICML 2018 An Efficient Semismooth Newton Based Algorithm for Convex Clustering Yancheng Yuan, Defeng Sun, Kim-Chuan Toh

JMLR 2017 A Unified Formulation and Fast Accelerated Proximal Gradient Method for Classification Naoki Ito, Akiko Takeda, Kim-Chuan Toh

CVPR 2016 Simultaneous Clustering and Model Selection for Tensor Affinities Zhuwen Li, Shuoguang Yang, Loong-Fah Cheong, Kim-Chuan Toh