Yi, Jinfeng

50 publications

JMLR 2025 Universal Online Convex Optimization Meets Second-Order Bounds Lijun Zhang, Yibo Wang, Guanghui Wang, Jinfeng Yi, Tianbao Yang

NeurIPS 2023 Efficient Algorithms for Generalized Linear Bandits with Heavy-Tailed Rewards Bo Xue, Yimu Wang, Yuanyu Wan, Jinfeng Yi, Lijun Zhang

ICML 2023 FedAvg Converges to Zero Training Loss Linearly for Overparameterized Multi-Layer Neural Networks Bingqing Song, Prashant Khanduri, Xinwei Zhang, Jinfeng Yi, Mingyi Hong

UAI 2023 Stochastic Graphical Bandits with Heavy-Tailed Rewards Yutian Gou, Jinfeng Yi, Lijun Zhang

AAAI 2023 Training Meta-Surrogate Model for Transferable Adversarial Attack Yunxiao Qin, Yuanhao Xiong, Jinfeng Yi, Cho-Jui Hsieh

ICML 2022 A Simple yet Universal Strategy for Online Convex Optimization Lijun Zhang, Guanghui Wang, Jinfeng Yi, Tianbao Yang

NeurIPS 2022 Can Adversarial Training Be Manipulated by Non-Robust Features? Lue Tao, Lei Feng, Hongxin Wei, Jinfeng Yi, Sheng-Jun Huang, Songcan Chen

ICLR 2022 How to Robustify Black-Box ML Models? a Zeroth-Order Optimization Perspective Yimeng Zhang, Yuguang Yao, Jinghan Jia, Jinfeng Yi, Mingyi Hong, Shiyu Chang, Sijia Liu

TMLR 2022 On the Adversarial Robustness of Vision Transformers Rulin Shao, Zhouxing Shi, Jinfeng Yi, Pin-Yu Chen, Cho-Jui Hsieh

NeurIPSW 2022 On the Adversarial Robustness of Vision Transformers Rulin Shao, Zhouxing Shi, Jinfeng Yi, Pin-Yu Chen, Cho-Jui Hsieh

NeurIPS 2022 Smoothed Online Convex Optimization Based on Discounted-Normal-Predictor Lijun Zhang, Wei Jiang, Jinfeng Yi, Tianbao Yang

ICML 2022 Understanding Clipping for Federated Learning: Convergence and Client-Level Differential Privacy Xinwei Zhang, Xiangyi Chen, Mingyi Hong, Steven Wu, Jinfeng Yi

AAAI 2022 With False Friends like These, Who Can Notice Mistakes? Lue Tao, Lei Feng, Jinfeng Yi, Songcan Chen

NeurIPS 2021 Better Safe than Sorry: Preventing Delusive Adversaries with Adversarial Training Lue Tao, Lei Feng, Jinfeng Yi, Sheng-Jun Huang, Songcan Chen

NeurIPS 2021 Fast Certified Robust Training with Short Warmup Zhouxing Shi, Yihan Wang, Huan Zhang, Jinfeng Yi, Cho-Jui Hsieh

ICMLW 2021 Fast Certified Robust Training with Short Warmup Zhouxing Shi, Yihan Wang, Huan Zhang, Jinfeng Yi, Cho-Jui Hsieh

ACML 2021 PFedAtt: Attention-Based Personalized Federated Learning on Heterogeneous Clients Zichen Ma, Yu Lu, Wenye Li, Jinfeng Yi, Shuguang Cui

AAAI 2020 A Frank-Wolfe Framework for Efficient and Effective Adversarial Attacks Jinghui Chen, Dongruo Zhou, Jinfeng Yi, Quanquan Gu

ICLR 2020 Improving Adversarial Robustness Requires Revisiting Misclassified Examples Yisen Wang, Difan Zou, Jinfeng Yi, James Bailey, Xingjun Ma, Quanquan Gu

AAAI 2020 Potential Passenger Flow Prediction: A Novel Study for Urban Transportation Development Yongshun Gong, Zhibin Li, Jian Zhang, Wei Liu, Jinfeng Yi

NeurIPS 2020 Provably Robust Metric Learning Lu Wang, Xuanqing Liu, Jinfeng Yi, Yuan Jiang, Cho-Jui Hsieh

AAAI 2020 Seq2Sick: Evaluating the Robustness of Sequence-to-Sequence Models with Adversarial Examples Minhao Cheng, Jinfeng Yi, Pin-Yu Chen, Huan Zhang, Cho-Jui Hsieh

MLJ 2020 Spanning Attack: Reinforce Black-Box Attacks with Unlabeled Data Lu Wang, Huan Zhang, Jinfeng Yi, Cho-Jui Hsieh, Yuan Jiang

AAAI 2019 AutoZOOM: Autoencoder-Based Zeroth Order Optimization Method for Attacking Black-Box Neural Networks Chun-Chen Tu, Pai-Shun Ting, Pin-Yu Chen, Sijia Liu, Huan Zhang, Jinfeng Yi, Cho-Jui Hsieh, Shin-Ming Cheng

NeurIPS 2019 DTWNet: A Dynamic Time Warping Network Xingyu Cai, Tingyang Xu, Jinfeng Yi, Junzhou Huang, Sanguthevar Rajasekaran

CVPRW 2019 Defending Against Adversarial Attacks Using Random Forest Yifan Ding, Liqiang Wang, Huan Zhang, Jinfeng Yi, Deliang Fan, Boqing Gong

IJCAI 2019 Improving the Robustness of Deep Neural Networks via Adversarial Training with Triplet Loss Pengcheng Li, Jinfeng Yi, Bowen Zhou, Lijun Zhang

ICML 2019 On the Convergence and Robustness of Adversarial Training Yisen Wang, Xingjun Ma, James Bailey, Jinfeng Yi, Bowen Zhou, Quanquan Gu

ICLR 2019 Query-Efficient Hard-Label Black-Box Attack: An Optimization-Based Approach Minhao Cheng, Thong Le, Pin-Yu Chen, Huan Zhang, JinFeng Yi, Cho-Jui Hsieh

IJCAI 2019 Similarity Preserving Representation Learning for Time Series Clustering Qi Lei, Jinfeng Yi, Roman Vaculín, Lingfei Wu, Inderjit S. Dhillon

ICLR 2019 Universal Stagewise Learning for Non-Convex Problems with Convergence on Averaged Solutions Zaiyi Chen, Zhuoning Yuan, Jinfeng Yi, Bowen Zhou, Enhong Chen, Tianbao Yang

NeurIPS 2018 Adaptive Negative Curvature Descent with Applications in Non-Convex Optimization Mingrui Liu, Zhe Li, Xiaoyu Wang, Jinfeng Yi, Tianbao Yang

AAAI 2018 EAD: Elastic-Net Attacks to Deep Neural Networks via Adversarial Examples Pin-Yu Chen, Yash Sharma, Huan Zhang, Jinfeng Yi, Cho-Jui Hsieh

ICLR 2018 Evaluating the Robustness of Neural Networks: An Extreme Value Theory Approach Tsui-Wei Weng, Huan Zhang, Pin-Yu Chen, Jinfeng Yi, Dong Su, Yupeng Gao, Cho-Jui Hsieh, Luca Daniel

ECCV 2018 Is Robustness the Cost of Accuracy? -- a Comprehensive Study on the Robustness of 18 Deep Image Classification Models Dong Su, Huan Zhang, Hongge Chen, Jinfeng Yi, Pin-Yu Chen, Yupeng Gao

AISTATS 2018 Random Warping Series: A Random Features Method for Time-Series Embedding Lingfei Wu, Ian En-Hsu Yen, Jinfeng Yi, Fangli Xu, Qi Lei, Michael Witbrock

IJCAI 2018 Self-Weighted Multiple Kernel Learning for Graph-Based Clustering and Semi-Supervised Classification Zhao Kang, Xiao Lu, Jinfeng Yi, Zenglin Xu

NeurIPS 2017 Improved Dynamic Regret for Non-Degenerate Functions Lijun Zhang, Tianbao Yang, Jinfeng Yi, Rong Jin, Zhi-Hua Zhou

NeurIPS 2017 Scalable Demand-Aware Recommendation Jinfeng Yi, Cho-Jui Hsieh, Kush R Varshney, Lijun Zhang, Yao Li

AAAI 2016 Stochastic Optimization for Kernel PCA Lijun Zhang, Tianbao Yang, Jinfeng Yi, Rong Jin, Zhi-Hua Zhou

ICML 2016 Tracking Slowly Moving Clairvoyant: Optimal Dynamic Regret of Online Learning with True and Noisy Gradient Tianbao Yang, Lijun Zhang, Rong Jin, Jinfeng Yi

MLJ 2015 Efficient Distance Metric Learning by Adaptive Sampling and Mini-Batch Stochastic Gradient Descent (SGD) Qi Qian, Rong Jin, Jinfeng Yi, Lijun Zhang, Shenghuo Zhu

ICML 2014 A Single-Pass Algorithm for Efficiently Recovering Sparse Cluster Centers of High-Dimensional Data Jinfeng Yi, Lijun Zhang, Jun Wang, Rong Jin, Anil Jain

ICML 2014 Efficient Algorithms for Robust One-Bit Compressive Sensing Lijun Zhang, Jinfeng Yi, Rong Jin

AAAI 2014 Privacy and Regression Model Preserved Learning Jinfeng Yi, Jun Wang, Rong Jin

ICML 2013 Online Kernel Learning with a near Optimal Sparsity Bound Lijun Zhang, Jinfeng Yi, Rong Jin, Ming Lin, Xiaofei He

ICML 2013 Semi-Supervised Clustering by Input Pattern Assisted Pairwise Similarity Matrix Completion Jinfeng Yi, Lijun Zhang, Rong Jin, Qi Qian, Anil Jain

AAAI 2012 Online Kernel Selection: Algorithms and Evaluations Tianbao Yang, Mehrdad Mahdavi, Rong Jin, Jinfeng Yi, Steven C. H. Hoi

NeurIPS 2012 Semi-Crowdsourced Clustering: Generalizing Crowd Labeling by Robust Distance Metric Learning Jinfeng Yi, Rong Jin, Shaili Jain, Tianbao Yang, Anil K. Jain

NeurIPS 2012 Stochastic Gradient Descent with Only One Projection Mehrdad Mahdavi, Tianbao Yang, Rong Jin, Shenghuo Zhu, Jinfeng Yi