Hongzhou Lin
Title
Cited by
Cited by
Year
A universal catalyst for first-order optimization
H Lin, J Mairal, Z Harchaoui
arXiv preprint arXiv:1506.02186, 2015
3832015
Resnet with one-neuron hidden layers is a universal approximator
H Lin, S Jegelka
arXiv preprint arXiv:1806.10909, 2018
982018
Catalyst acceleration for first-order convex optimization: from theory to practice
H Lin, J Mairal, Z Harchaoui
Journal of Machine Learning Research 18 (1), 7854-7907, 2018
782018
Catalyst for gradient-based nonconvex optimization
C Paquette, H Lin, D Drusvyatskiy, J Mairal, Z Harchaoui
International Conference on Artificial Intelligence and Statistics, 613-622, 2018
72*2018
An inexact variable metric proximal point algorithm for generic quasi-Newton acceleration
H Lin, J Mairal, Z Harchaoui
SIAM Journal on Optimization 29 (2), 1408-1443, 2019
22*2019
Complexity of Finding Stationary Points of Nonsmooth Nonconvex Functions
J Zhang, H Lin, S Jegelka, A Jadbabaie, S Sra
arXiv preprint arXiv:2002.04130, 2020
72020
Ideal: Inexact decentralized accelerated augmented lagrangian method
Y Arjevani, J Bruna, B Can, M Gürbüzbalaban, S Jegelka, H Lin
arXiv preprint arXiv:2006.06733, 2020
42020
On the Complexity of Minimizing Convex Finite Sums Without Using the Indices of the Individual Functions
Y Arjevani, A Daniely, S Jegelka, H Lin
arXiv preprint arXiv:2002.03273, 2020
12020
Complexity of Finding Stationary Points of Nonconvex Nonsmooth Functions
J Zhang, H Lin, S Jegelka, S Sra, A Jadbabaie
International Conference on Machine Learning, 11173-11182, 2020
2020
Stochastic Optimization with Non-stationary Noise
J Zhang, H Lin, S Das, S Sra, A Jadbabaie
arXiv preprint arXiv:2006.04429, 2020
2020
Perceptual Regularization: Visualizing and Learning Generalizable Representations
H Lin, J Robinson, S Jegelka
2019
Algorithmes d'accélération générique pour les méthodes d'optimisation en apprentissage statistique
H Lin
Université Grenoble Alpes (ComUE), 2017
2017
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Articles 1–12