Meixia LIN
Meixia LIN
Assistant Professor, Engineering Systems and Design, Singapore University of Technology and Design
Verified email at - Homepage
Cited by
Cited by
Efficient sparse semismooth Newton methods for the clustered Lasso problem
M Lin, YJ Liu, D Sun, KC Toh
SIAM Journal on Optimization 29 (3), 2026-2052, 2019
An augmented Lagrangian method with constraint generation for shape-constrained convex regression problems
M Lin, D Sun, KC Toh
Mathematical Programming Computation, 2021
Signal analysis via the stochastic geometry of spectrogram level sets
S Ghosh, M Lin, D Sun
IEEE Transactions on Signal Processing 70, 1104-1117, 2022
Adaptive sieving with ppdna: Generating solution paths of exclusive lasso models
M Lin, Y Yuan, D Sun, KC Toh
arXiv preprint arXiv:2009.08719, 2020
Determinantal point processes based on orthogonal polynomials for sampling minibatches in SGD
R Bardenet, S Ghosh, M Lin
Advances in Neural Information Processing Systems 34, 16226-16237, 2021
Estimation of sparse Gaussian graphical models with hidden clustering structure
M Lin, D Sun, KC Toh, C Wang
arXiv preprint arXiv:2004.08115, 2020
A positive and moment-preserving Fourier spectral method
Z Cai, B Lin, M Lin
SIAM Journal on Numerical Analysis 62 (1), 273-294, 2024
Adaptive sieving: A dimension reduction technique for sparse optimization problems
Y Yuan, M Lin, D Sun, KC Toh
arXiv preprint arXiv:2306.17369, 2023
A highly efficient algorithm for solving exclusive lasso problems
M Lin, Y Yuan, D Sun, KC Toh
Optimization Methods and Software, 1-30, 2023
Wasserstein distributionally robust optimization and its tractable regularization formulations
H Chu, M Lin, KC Toh
arXiv preprint arXiv:2402.03942, 2024
Learning the hub graphical Lasso model with the structured sparsity via an efficient algorithm
C Wang, P Tang, W He, M Lin
arXiv preprint arXiv:2308.08852, 2023
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