Kim-Chuan Toh
17 papers · 2016–2025 · 6 venues · across top CS/AI venues
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Achievements
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πΊοΈ Taxonomy Completionist (25) π Academic Marathon Β· Sprint π Conference Polyglot Β· Silver π Interdisciplinary Bridge Β· Bronze π£ Hot Topic Early Bird
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(12)
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(4)
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Top co-authors
Research topics
Keywords
semismooth newton method
(4)
augmented lagrangian method
(4)
optimal transport
(3)
stochastic optimization
(3)
semismooth newton
(3)
non-convex optimization
(2)
square-root loss
(2)
entropy regularization
(2)
convex optimization
(2)
neural network training
(2)
convex clustering
(2)
alternating direction method of multiplier
(2)
proximal point method
(2)
clustering optimization
(1)
feature selection
(1)
logistic regression
(1)
model selection
(1)
stochastic gradient descent
(1)
continuous optimization
(1)
matrix factorization
(1)
Papers
Memory-Efficient 4-bit Preconditioned Stochastic Optimization
ICCV 2025
Nonconvex Stochastic Bregman Proximal Gradient Method with Application to Deep Learning
JMLR 2025
Towards Understanding Why FixMatch Generalizes Better Than Supervised Learning
ICLR 2025
Accelerating Nuclear-norm Regularized Low-rank Matrix Optimization Through Burer-Monteiro Decomposition
JMLR 2024
Adam-family Methods for Nonsmooth Optimization with Convergence Guarantees
JMLR 2024
Estimation of Sparse Gaussian Graphical Models with Hidden Clustering Structure
JMLR 2024
On Efficient and Scalable Computation of the Nonparametric Maximum Likelihood Estimator in Mixture Models
JMLR 2024
On Partial Optimal Transport: Revising the Infeasibility of Sinkhorn and Efficient Gradient Methods
AAAI 2024
Win: Weight-Decay-Integrated Nesterov Acceleration for Faster Network Training
JMLR 2024
On Regularized Square-root Regression Problems: Distributionally Robust Interpretation and Fast Computations
JMLR 2022
A Fast Globally Linearly Convergent Algorithm for the Computation of Wasserstein Barycenters
JMLR 2021
Convex Clustering: Model, Theoretical Guarantee and Efficient Algorithm
JMLR 2021
A Sparse Semismooth Newton Based Proximal Majorization-Minimization Algorithm for Nonconvex Square-Root-Loss Regression Problems
JMLR 2020
Solving the OSCAR and SLOPE Models Using a Semismooth Newton-Based Augmented Lagrangian Method
JMLR 2019
An Efficient Semismooth Newton based Algorithm for Convex Clustering
ICML 2018
A Unified Formulation and Fast Accelerated Proximal Gradient Method for Classification
JMLR 2017
Simultaneous Clustering and Model Selection for Tensor Affinities
CVPR 2016