Hongzhou Lin - RankMe

26 papers A* 7A 1Journal 15Unranked 2

Year	Rank	Type	Title / Venue / Authors
2025	A*	`conf`	From Sparse Dependence to Sparse Attention: Unveiling How Chain-of-Thought Enhances Transformer Sample Efficiency. ICLR Kaiyue Wen, Huaqing Zhang, Hongzhou Lin, Jingzhao Zhang
2025	J	`jnl`	Goedel-Prover-V2: Scaling Formal Theorem Proving with Scaffolded Data Synthesis and Self-Correction. CoRR Yong Lin, Shange Tang, Bohan Lyu, Ziran Yang, Jui-Hui Chung, Haoyu Zhao, Lai Jiang, Yihan Geng, Jiawei Ge, Jingruo Sun, Jiayun Wu, Jiri Gesi, Ximing Lu, David Acuna, Kaiyu Yang, Hongzhou Lin, Yejin Choi, Danqi Chen, Sanjeev Arora, Chi Jin
2025	J	`jnl`	Goedel-Prover: A Frontier Model for Open-Source Automated Theorem Proving. CoRR Yong Lin, Shange Tang, Bohan Lyu, Jiayun Wu, Hongzhou Lin, Kaiyu Yang, Jia Li, Mengzhou Xia, Danqi Chen, Sanjeev Arora, Chi Jin
2025	J	`jnl`	Ineq-Comp: Benchmarking Human-Intuitive Compositional Reasoning in Automated Theorem Proving on Inequalities. CoRR Haoyu Zhao, Yihan Geng, Shange Tang, Yong Lin, Bohan Lyu, Hongzhou Lin, Chi Jin, Sanjeev Arora
2025	J	`jnl`	QuestA: Expanding Reasoning Capacity in LLMs via Question Augmentation. CoRR Jiazheng Li, Hong Lu, Kaiyue Wen, Zaiwen Yang, Jiaxuan Gao, Hongzhou Lin, Yi Wu, Jingzhao Zhang
2025	J	`jnl`	Task Generalization With AutoRegressive Compositional Structure: Can Learning From CoRR Amirhesam Abedsoltan, Huaqing Zhang, Kaiyue Wen, Hongzhou Lin, Jingzhao Zhang, Mikhail Belkin
2025	A*	`conf`	Task Generalization with Autoregressive Compositional Structure: Can Learning from D Tasks Generalize to DT Tasks? ICML Amirhesam Abedsoltan, Huaqing Zhang, Kaiyue Wen, Hongzhou Lin, Jingzhao Zhang, Mikhail Belkin
2025	—	`conf`	UNDIAL: Self-Distillation with Adjusted Logits for Robust Unlearning in Large Language Models. NAACL (Long Papers) Yijiang River Dong, Hongzhou Lin, Mikhail Belkin, Ramón Huerta, Ivan Vulic
2024	J	`jnl`	From Sparse Dependence to Sparse Attention: Unveiling How Chain-of-Thought Enhances Transformer Sample Efficiency. CoRR Kaiyue Wen, Huaqing Zhang, Hongzhou Lin, Jingzhao Zhang
2024	J	`jnl`	Unmemorization in Large Language Models via Self-Distillation and Deliberate Imagination. CoRR Yijiang River Dong, Hongzhou Lin, Mikhail Belkin, Ramón Huerta, Ivan Vulic
2023	J	`jnl`	Deep hybrid model with satellite imagery: how to combine demand modeling and computer vision for behavior analysis? CoRR Qingyi Wang, Shenhao Wang, Yunhan Zheng, Hongzhou Lin, Xiaohu Zhang, Jinhua Zhao, Joan Walker
2022	A*	`conf`	Beyond Worst-Case Analysis in Stochastic Approximation: Moment Estimation Improves Instance Complexity. ICML Jingzhao Zhang, Hongzhou Lin, Subhro Das, Suvrit Sra, Ali Jadbabaie
2021	A*	`conf`	Delayed Gradient Averaging: Tolerate the Communication Latency for Federated Learning. NeurIPS Ligeng Zhu, Hongzhou Lin, Yao Lu, Yujun Lin, Song Han
2020	A*	`conf`	Complexity of Finding Stationary Points of Nonconvex Nonsmooth Functions. ICML Jingzhao Zhang, Hongzhou Lin, Stefanie Jegelka, Suvrit Sra, Ali Jadbabaie
2020	A*	`conf`	IDEAL: Inexact DEcentralized Accelerated Augmented Lagrangian Method. NeurIPS Yossi Arjevani, Joan Bruna, Bugra Can, Mert Gürbüzbalaban, Stefanie Jegelka, Hongzhou Lin
2020	J	`jnl`	IDEAL: Inexact DEcentralized Accelerated Augmented Lagrangian Method. CoRR Yossi Arjevani, Joan Bruna, Bugra Can, Mert Gürbüzbalaban, Stefanie Jegelka, Hongzhou Lin
2020	J	`jnl`	On Complexity of Finding Stationary Points of Nonsmooth Nonconvex Functions. CoRR Jingzhao Zhang, Hongzhou Lin, Suvrit Sra, Ali Jadbabaie
2020	J	`jnl`	On the Complexity of Minimizing Convex Finite Sums Without Using the Indices of the Individual Functions. CoRR Yossi Arjevani, Amit Daniely, Stefanie Jegelka, Hongzhou Lin
2020	J	`jnl`	Stochastic Optimization with Non-stationary Noise. CoRR Jingzhao Zhang, Hongzhou Lin, Subhro Das, Suvrit Sra, Ali Jadbabaie
2019	J	`jnl`	An Inexact Variable Metric Proximal Point Algorithm for Generic Quasi-Newton Acceleration. SIAM J. Optim. Hongzhou Lin, Julien Mairal, Zaïd Harchaoui
2018	A	`conf`	Catalyst for Gradient-based Nonconvex Optimization. AISTATS Courtney Paquette, Hongzhou Lin, Dmitriy Drusvyatskiy, Julien Mairal, Zaïd Harchaoui
2018	A*	`conf`	ResNet with one-neuron hidden layers is a Universal Approximator. NeurIPS Hongzhou Lin, Stefanie Jegelka
2018	J	`jnl`	ResNet with one-neuron hidden layers is a Universal Approximator. CoRR Hongzhou Lin, Stefanie Jegelka
2017	J	`jnl`	Catalyst Acceleration for First-order Convex Optimization: from Theory to Practice. J. Mach. Learn. Res. Hongzhou Lin, Julien Mairal, Zaïd Harchaoui
2017	—	`—`	Generic acceleration schemes for gradient-based optimization in machine learning. (Algorithmes d'accélération générique pour les méthodes d'optimisation en apprentissage statistique). Hongzhou Lin
2015	—	`conf`	A Universal Catalyst for First-Order Optimization. NIPS Hongzhou Lin, Julien Mairal, Zaïd Harchaoui