Cong Fang

Publication Activity (10 Years)

Years Active: 2014-2024
Publications (10 Years): 47

Top Topics

Linear Least Squares

Electronic Nose

Alternating Direction Method Of Multipliers

Top Venues

Publications

Yexin Zhang, Chenyi Zhang, Cong Fang, Liwei Wang, Tongyang Li
Quantum Algorithms and Lower Bounds for Finite-Sum Optimization. CoRR (2024)
Long Yang, Zhixiong Huang, Fenghao Lei, Yucun Zhong, Yiming Yang, Cong Fang, Shiting Wen, Binbin Zhou, Zhouchen Lin
Policy Representation via Diffusion Probability Model for Reinforcement Learning. CoRR (2023)
Pengyun Yue, Hanzhen Zhao, Cong Fang, Di He, Liwei Wang, Zhouchen Lin, Song-chun Zhu
CORE: Common Random Reconstruction for Distributed Optimization with Provable Low Communication Complexity. CoRR (2023)
Jianqing Fan, Cong Fang, Yihong Gu, Tong Zhang
Environment Invariant Linear Least Squares. CoRR (2023)
Yuanshi Liu, Cong Fang, Tong Zhang
Double Randomized Underdamped Langevin with Dimension-Independent Convergence Guarantee. NeurIPS (2023)
Mingyuan Zhang, Zhaolin Cheng, Sheung Ting Ramona Shiu, Jiacheng Liang, Cong Fang, Zhengtao Ma, Le Fang, Stephen Jia Wang
Towards Human-Centred AI-Co-Creation: A Three-Level Framework for Effective Collaboration between Human and AI. CSCW Companion (2023)
Pengyun Yue, Cong Fang, Zhouchen Lin
On the Lower Bound of Minimizing Polyak-Łojasiewicz functions. COLT (2023)
Jianghui Wang, Cheng Yang, Xingyu Xie, Cong Fang, Zhouchen Lin
Task-Robust Pre-Training for Worst-Case Downstream Adaptation. CoRR (2023)
Shihong Ding, Hanze Dong, Cong Fang, Zhouchen Lin, Tong Zhang
Provable Particle-based Primal-Dual Algorithm for Mixed Nash Equilibrium. CoRR (2023)
Pengyun Yue, Long Yang, Cong Fang, Zhouchen Lin
Zeroth-order Optimization with Weak Dimension Dependency. COLT (2023)
Jianghui Wang, Yang Chen, Xingyu Xie, Cong Fang, Zhouchen Lin
Task-Robust Pre-Training for Worst-Case Downstream Adaptation. NeurIPS (2023)
Yuanshi Liu, Hanzhen Zhao, Yang Xu, Pengyun Yue, Cong Fang
Accelerated Gradient Algorithms with Adaptive Subspace Search for Instance-Faster Optimization. CoRR (2023)
Cong Fang, Yihong Gu, Weizhong Zhang, Tong Zhang
Convex Formulation of Overparameterized Deep Neural Networks. IEEE Trans. Inf. Theory 68 (8) (2022)
Cong Fang, Hua-Yao Li, Long Li, Hu-Yin Su, Jiang Tang, Xiang Bai, Huan Liu
Smart Electronic Nose Enabled by an All-Feature Olfactory Algorithm. Adv. Intell. Syst. 4 (7) (2022)
Jia Li, Mingqing Xiao, Cong Fang, Yue Dai, Chao Xu, Zhouchen Lin
Training Neural Networks by Lifted Proximal Operator Machines. IEEE Trans. Pattern Anal. Mach. Intell. 44 (6) (2022)
Cong Fang, Hua-Yao Li, Long Li, Hu-Yin Su, Jiang Tang, Xiang Bai, Huan Liu
Smart Electronic Nose Enabled by an All-Feature Olfactory Algorithm. Adv. Intell. Syst. 4 (7) (2022)
Shi Gong, Huan Zhou, Feng Xue, Cong Fang, Yiqun Li, Yu Zhou
FastRoadSeg: Fast Monocular Road Segmentation Network. IEEE Trans. Intell. Transp. Syst. 23 (11) (2022)
Cong Fang, Hangfeng He, Qi Long, Weijie J. Su
Layer-Peeled Model: Toward Understanding Well-Trained Deep Neural Networks. CoRR (2021)
Cong Fang, Jason D. Lee, Pengkun Yang, Tong Zhang
Modeling from Features: a Mean-field Framework for Over-parameterized Deep Neural Networks. COLT (2021)
Cong Fang, Song Bai, Qianlan Chen, Yu Zhou, Liming Xia, Lixin Qin, Shi Gong, Xudong Xie, Chunhua Zhou, Dandan Tu, Changzheng Zhang, Xiaowu Liu, Weiwei Chen, Xiang Bai, Philip H. S. Torr
Deep learning for predicting COVID-19 malignant progression. Medical Image Anal. 72 (2021)
Cong Fang, Hanze Dong, Tong Zhang
Mathematical Models of Overparameterized Neural Networks. Proc. IEEE 109 (5) (2021)
Huan Li, Cong Fang, Zhouchen Lin
Accelerated First-Order Optimization Algorithms for Machine Learning. Proc. IEEE 108 (11) (2020)
Huan Li, Cong Fang, Wotao Yin, Zhouchen Lin
Decentralized Accelerated Gradient Methods With Increasing Penalty Parameters. IEEE Trans. Signal Process. 68 (2020)
Bohang Zhang, Jikai Jin, Cong Fang, Liwei Wang
Improved Analysis of Clipping Algorithms for Non-convex Optimization. CoRR (2020)
Cong Fang, Jason D. Lee, Pengkun Yang, Tong Zhang
Modeling from Features: a Mean-field Framework for Over-parameterized Deep Neural Networks. CoRR (2020)
Bohang Zhang, Jikai Jin, Cong Fang, Liwei Wang
Improved Analysis of Clipping Algorithms for Non-convex Optimization. NeurIPS (2020)
Yihong Gu, Weizhong Zhang, Cong Fang, Jason D. Lee, Tong Zhang
How to Characterize The Landscape of Overparameterized Convolutional Neural Networks. NeurIPS (2020)
Cong Fang, Hanze Dong, Tong Zhang
Mathematical Models of Overparameterized Neural Networks. CoRR (2020)
Cong Fang, Zhouchen Lin, Tong Zhang
Sharp Analysis for Nonconvex SGD Escaping from Saddle Points. CoRR (2019)
Feng Zhang, Linan Li, Qiang Huo, Cong Fang, Wenqiang Ba
A Fluctuation Model of a Hf02 RRAM Cell for Memory Circuit Designs. SMACD (2019)
Zebang Shen, Cong Fang, Peilin Zhao, Junzhou Huang, Hui Qian
Complexities in Projection-Free Stochastic Non-convex Minimization. AISTATS (2019)
Cong Fang, Zhouchen Lin, Tong Zhang
Sharp Analysis for Nonconvex SGD Escaping from Saddle Points. COLT (2019)
Cong Fang, Hanze Dong, Tong Zhang
Over Parameterized Two-level Neural Networks Can Learn Near Optimal Feature Representations. CoRR (2019)
Cong Fang, Yihong Gu, Weizhong Zhang, Tong Zhang
Convex Formulation of Overparameterized Deep Neural Networks. CoRR (2019)
Jia Li, Cong Fang, Zhouchen Lin
Lifted Proximal Operator Machines. AAAI (2019)
Zhenyu Zhao, Chenping Hou, Bo Lin, Cong Fang
Learning Compact Partial Differential Equations for Color Images with Efficiency. ICASSP (2019)
Jia Li, Cong Fang, Zhouchen Lin
Lifted Proximal Operator Machines. CoRR (2018)
Pan Zhou, Cong Fang, Zhouchen Lin, Chao Zhang, Edward Y. Chang
Dictionary learning with structured noise. Neurocomputing 273 (2018)
Haishan Ye, Zhichao Huang, Cong Fang, Chris Junchi Li, Tong Zhang
Hessian-Aware Zeroth-Order Optimization for Black-Box Adversarial Attack. CoRR (2018)
Cong Fang, Yameng Huang, Zhouchen Lin
Accelerating Asynchronous Algorithms for Convex Optimization by Momentum Compensation. CoRR (2018)
Cong Fang, Chris Junchi Li, Zhouchen Lin, Tong Zhang
SPIDER: Near-Optimal Non-Convex Optimization via Stochastic Path Integrated Differential Estimator. CoRR (2018)
Cong Fang, Chris Junchi Li, Zhouchen Lin, Tong Zhang
SPIDER: Near-Optimal Non-Convex Optimization via Stochastic Path-Integrated Differential Estimator. NeurIPS (2018)
Cong Fang, Feng Cheng, Zhouchen Lin
Faster and Non-ergodic O(1/K) Stochastic Alternating Direction Method of Multipliers. NIPS (2017)
Cong Fang, Zhouchen Lin
Parallel Asynchronous Stochastic Variance Reduction for Nonconvex Optimization. AAAI (2017)
Cong Fang, Zhenyu Zhao, Pan Zhou, Zhouchen Lin
Feature learning via partial differential equation with applications to face recognition. Pattern Recognit. 69 (2017)
Feng Zhang, Dongyu Fan, Yuan Duan, Jin Li, Cong Fang, Yun Li, Xiaowei Han, Lan Dai, Cheng-Ying Chen, Jinshun Bi, Ming Liu, Meng-Fan Chang
A 130nm 1Mb HfOx embedded RRAM macro using self-adaptive peripheral circuit system techniques for 1.6X work temperature range. A-SSCC (2017)
Zhenyu Zhao, Cong Fang, Zhouchen Lin, Yi Wu
A robust hybrid method for text detection in natural scenes by learning-based partial differential equations. Neurocomputing 168 (2015)
Jiaoyan Chen, Guozhou Zheng, Cong Fang, Ningyu Zhang, Huajun Chen, Zhaohui Wu
Time-series processing of large scale remote sensing data with extreme learning machine. Neurocomputing 128 (2014)