Kim-Chuan Toh
17 papers · 2016–2025 · 6 conferences · across top CS/AI conferences
Achievements
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π£ Hot Topic Early Bird πΊοΈ Taxonomy Completionist (10) π Interdisciplinary Bridge π§ Keyword Pioneer π Conference Polyglot (6)
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Hot Topic Early Bird
π
Interdisciplinary Bridge
π¬
Deep Specialist
(10)
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Keyword Champion
(3)
ποΈ
Keyword Collector
(86)
π
Century Club
(17)
π₯
Unstoppable
(7)
β‘
Prolific Year
(6)
Conferences
JMLR (12)
AAAI (1)
CVPR (1)
ICCV (1)
ICLR (1)
ICML (1)
Top co-authors
Keywords
semismooth newton method
(4)
augmented lagrangian method
(4)
stochastic optimization
(3)
semismooth newton
(3)
optimal transport
(3)
nonconvex optimization
(2)
neural network training
(2)
convex optimization
(2)
square-root loss
(2)
convex clustering
(2)
alternating direction method of multiplier
(2)
entropy regularization
(2)
sample complexity
(1)
binary classification
(1)
clustering optimization
(1)
feature selection
(1)
stochastic gradient descent
(1)
logistic regression
(1)
l1 regularization
(1)
matrix factorization
(1)
Papers
Towards Understanding Why FixMatch Generalizes Better Than Supervised Learning
ICLR 2025
Nonconvex Stochastic Bregman Proximal Gradient Method with Application to Deep Learning
JMLR 2025
Memory-Efficient 4-bit Preconditioned Stochastic Optimization
ICCV 2025
On Partial Optimal Transport: Revising the Infeasibility of Sinkhorn and Efficient Gradient Methods
AAAI 2024
On Efficient and Scalable Computation of the Nonparametric Maximum Likelihood Estimator in Mixture Models
JMLR 2024
Adam-family Methods for Nonsmooth Optimization with Convergence Guarantees
JMLR 2024
Win: Weight-Decay-Integrated Nesterov Acceleration for Faster Network Training
JMLR 2024
Estimation of Sparse Gaussian Graphical Models with Hidden Clustering Structure
JMLR 2024
Accelerating Nuclear-norm Regularized Low-rank Matrix Optimization Through Burer-Monteiro Decomposition
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