Fang, Cong

25 publications

NeurIPS 2025 Improving Model Representation and Reducing KV Cache via Skip Connections with First Value Heads Zhoutong Wu, Yuan Zhang, Yiming Dong, Chenheng Zhang, Cong Fang, Kun Yuan, Zhouchen Lin

ICML 2025 Learning Curves of Stochastic Gradient Descent in Kernel Regression Haihan Zhang, Weicheng Lin, Yuanshi Liu, Cong Fang

NeurIPS 2025 PaZO: Preconditioned Accelerated Zeroth-Order Optimization for Fine-Tuning LLMs Hanzhen Zhao, Shihong Ding, Cong Fang, Zhouchen Lin

ICLR 2025 SEPARATE: A Simple Low-Rank Projection for Gradient Compression in Modern Large-Scale Model Training Process Hanzhen Zhao, Xingyu Xie, Cong Fang, Zhouchen Lin

ICML 2024 End-to-End Neuro-Symbolic Reinforcement Learning with Textual Explanations Lirui Luo, Guoxi Zhang, Hongming Xu, Yaodong Yang, Cong Fang, Qing Li

NeurIPS 2024 Optimizing over Multiple Distributions Under Generalized Quasar-Convexity Condition Shihong Ding, Long Yang, Luo Luo, Cong Fang

JMLR 2024 PAPAL: A Provable PArticle-Based Primal-Dual ALgorithm for Mixed Nash Equilibrium Shihong Ding, Hanze Dong, Cong Fang, Zhouchen Lin, Tong Zhang

ICML 2024 Quantum Algorithms and Lower Bounds for Finite-Sum Optimization Yexin Zhang, Chenyi Zhang, Cong Fang, Liwei Wang, Tongyang Li

ICML 2024 Relational Learning in Pre-Trained Models: A Theory from Hypergraph Recovery Perspective Yang Chen, Cong Fang, Zhouchen Lin, Bing Liu

NeurIPS 2024 Separation and Bias of Deep Equilibrium Models on Expressivity and Learning Dynamics Zhoutong Wu, Yimu Zhang, Cong Fang, Zhouchen Lin

NeurIPS 2024 The Implicit Bias of Heterogeneity Towards Invariance: A Study of Multi-Environment Matrix Sensing Yang Xu, Yihong Gu, Cong Fang

NeurIPS 2023 Double Randomized Underdamped Langevin with Dimension-Independent Convergence Guarantee Yuanshi Liu, Cong Fang, Tong Zhang

COLT 2023 On the Lower Bound of Minimizing Polyak-Łojasiewicz Functions Pengyun Yue, Cong Fang, Zhouchen Lin

NeurIPS 2023 Task-Robust Pre-Training for Worst-Case Downstream Adaptation Jianghui Wang, Yang Chen, Xingyu Xie, Cong Fang, Zhouchen Lin

COLT 2023 Zeroth-Order Optimization with Weak Dimension Dependency Pengyun Yue, Long Yang, Cong Fang, Zhouchen Lin

COLT 2021 Modeling from Features: A Mean-Field Framework for Over-Parameterized Deep Neural Networks Cong Fang, Jason Lee, Pengkun Yang, Tong Zhang

ICLR 2020 A Stochastic Trust Region Method for Non-Convex Minimization Zebang Shen, Pan Zhou, Cong Fang, Alejandro Ribeiro

NeurIPS 2020 How to Characterize the Landscape of Overparameterized Convolutional Neural Networks Yihong Gu, Weizhong Zhang, Cong Fang, Jason Lee, Tong Zhang

NeurIPS 2020 Improved Analysis of Clipping Algorithms for Non-Convex Optimization Bohang Zhang, Jikai Jin, Cong Fang, Liwei Wang

AISTATS 2019 Complexities in Projection-Free Stochastic Non-Convex Minimization Zebang Shen, Cong Fang, Peilin Zhao, Junzhou Huang, Hui Qian

AAAI 2019 Lifted Proximal Operator Machines Jia Li, Cong Fang, Zhouchen Lin

COLT 2019 Sharp Analysis for Nonconvex SGD Escaping from Saddle Points Cong Fang, Zhouchen Lin, Tong Zhang

NeurIPS 2018 SPIDER: Near-Optimal Non-Convex Optimization via Stochastic Path-Integrated Differential Estimator Cong Fang, Chris Junchi Li, Zhouchen Lin, Tong Zhang

NeurIPS 2017 Faster and Non-Ergodic O(1/K) Stochastic Alternating Direction Method of Multipliers Cong Fang, Feng Cheng, Zhouchen Lin

AAAI 2017 Parallel Asynchronous Stochastic Variance Reduction for Nonconvex Optimization Cong Fang, Zhouchen Lin