Hongzhou Lin

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 15

Top Venues

CoRR

NeurIPS

ICML

AISTATS

Grenoble Alpes University, France (PHD)

Education History

Grenoble Alpes University, France

PHD

Publications

Yijiang River Dong, Hongzhou Lin, Mikhail Belkin, Ramón Huerta, Ivan Vulic
Unmemorization in Large Language Models via Self-Distillation and Deliberate Imagination. CoRR (2024)
Qingyi Wang, Shenhao Wang, Yunhan Zheng, Hongzhou Lin, Xiaohu Zhang, Jinhua Zhao, Joan Walker
Deep hybrid model with satellite imagery: how to combine demand modeling and computer vision for behavior analysis? CoRR (2023)
Jingzhao Zhang, Hongzhou Lin, Subhro Das, Suvrit Sra, Ali Jadbabaie
Beyond Worst-Case Analysis in Stochastic Approximation: Moment Estimation Improves Instance Complexity. ICML (2022)
Ligeng Zhu, Hongzhou Lin, Yao Lu, Yujun Lin, Song Han
Delayed Gradient Averaging: Tolerate the Communication Latency for Federated Learning. NeurIPS (2021)
Jingzhao Zhang, Hongzhou Lin, Suvrit Sra, Ali Jadbabaie
On Complexity of Finding Stationary Points of Nonsmooth Nonconvex Functions. CoRR (2020)
Yossi Arjevani, Joan Bruna, Bugra Can, Mert Gürbüzbalaban, Stefanie Jegelka, Hongzhou Lin
IDEAL: Inexact DEcentralized Accelerated Augmented Lagrangian Method. CoRR (2020)
Yossi Arjevani, Amit Daniely, Stefanie Jegelka, Hongzhou Lin
On the Complexity of Minimizing Convex Finite Sums Without Using the Indices of the Individual Functions. CoRR (2020)
Jingzhao Zhang, Hongzhou Lin, Subhro Das, Suvrit Sra, Ali Jadbabaie
Stochastic Optimization with Non-stationary Noise. CoRR (2020)
Yossi Arjevani, Joan Bruna, Bugra Can, Mert Gürbüzbalaban, Stefanie Jegelka, Hongzhou Lin
IDEAL: Inexact DEcentralized Accelerated Augmented Lagrangian Method. NeurIPS (2020)
Jingzhao Zhang, Hongzhou Lin, Stefanie Jegelka, Suvrit Sra, Ali Jadbabaie
Complexity of Finding Stationary Points of Nonconvex Nonsmooth Functions. ICML (2020)
Hongzhou Lin, Julien Mairal, Zaïd Harchaoui
An Inexact Variable Metric Proximal Point Algorithm for Generic Quasi-Newton Acceleration. SIAM J. Optim. 29 (2) (2019)
Hongzhou Lin, Stefanie Jegelka
ResNet with one-neuron hidden layers is a Universal Approximator. NeurIPS (2018)
Courtney Paquette, Hongzhou Lin, Dmitriy Drusvyatskiy, Julien Mairal, Zaïd Harchaoui
Catalyst for Gradient-based Nonconvex Optimization. AISTATS (2018)
Hongzhou Lin, Stefanie Jegelka
ResNet with one-neuron hidden layers is a Universal Approximator. CoRR (2018)
Hongzhou Lin, Julien Mairal, Zaïd Harchaoui
Catalyst Acceleration for First-order Convex Optimization: from Theory to Practice. J. Mach. Learn. Res. 18 (2017)
Hongzhou Lin, Julien Mairal, Zaïd Harchaoui
A Universal Catalyst for First-Order Optimization. NIPS (2015)

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Publication Activity (10 Years)

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Hongzhou Lin