Jinfeng Yi

ORCID

Publication Activity (10 Years)

Years Active: 2012-2023
Publications (10 Years): 118

Top Venues

Publications

Bo Li, Peng Qi, Bo Liu, Shuai Di, Jingen Liu, Jiquan Pei, Jinfeng Yi, Bowen Zhou
Trustworthy AI: From Principles to Practices. ACM Comput. Surv. 55 (9) (2023)
Qi Liu, Jinze Wu, Zhenya Huang, Hao Wang, Yuting Ning, Ming Chen, Enhong Chen, Jinfeng Yi, Bowen Zhou
Federated User Modeling from Hierarchical Information. ACM Trans. Inf. Syst. 41 (2) (2023)
Bo Xue, Yimu Wang, Yuanyu Wan, Jinfeng Yi, Lijun Zhang
Efficient Algorithms for Generalized Linear Bandits with Heavy-tailed Rewards. CoRR (2023)
Yunxiao Qin, Yuanhao Xiong, Jinfeng Yi, Cho-Jui Hsieh
Training Meta-Surrogate Model for Transferable Adversarial Attack. AAAI (2023)
Bingqing Song, Prashant Khanduri, Xinwei Zhang, Jinfeng Yi, Mingyi Hong
FedAvg Converges to Zero Training Loss Linearly for Overparameterized Multi-Layer Neural Networks. ICML (2023)
Bo Xue, Yimu Wang, Yuanyu Wan, Jinfeng Yi, Lijun Zhang
Efficient Algorithms for Generalized Linear Bandits with Heavy-tailed Rewards. NeurIPS (2023)
Yutian Gou, Jinfeng Yi, Lijun Zhang
Stochastic Graphical Bandits with Heavy-Tailed Rewards. UAI (2023)
Xinwei Zhang, Xiangyi Chen, Mingyi Hong, Steven Wu, Jinfeng Yi
Understanding Clipping for Federated Learning: Convergence and Client-Level Differential Privacy. ICML (2022)
Lue Tao, Lei Feng, Hongxin Wei, Jinfeng Yi, Sheng-Jun Huang, Songcan Chen
Can Adversarial Training Be Manipulated By Non-Robust Features? CoRR (2022)
Rulin Shao, Zhouxing Shi, Jinfeng Yi, Pin-Yu Chen, Cho-Jui Hsieh
Robust Text CAPTCHAs Using Adversarial Examples. Big Data (2022)
Lue Tao, Lei Feng, Hongxin Wei, Jinfeng Yi, Sheng-Jun Huang, Songcan Chen
Can Adversarial Training Be Manipulated By Non-Robust Features? NeurIPS (2022)
Rulin Shao, Zhouxing Shi, Jinfeng Yi, Pin-Yu Chen, Cho-Jui Hsieh
On the Adversarial Robustness of Vision Transformers. Trans. Mach. Learn. Res. 2022 (2022)
Lijun Zhang, Wei Jiang, Jinfeng Yi, Tianbao Yang
Smoothed Online Convex Optimization Based on Discounted-Normal-Predictor. NeurIPS (2022)
Yingchun Jian, Jinfeng Yi, Lijun Zhang
Adaptive Feature Generation for Online Continual Learning from Imbalanced Data. PAKDD (1) (2022)
Yimeng Zhang, Yuguang Yao, Jinghan Jia, Jinfeng Yi, Mingyi Hong, Shiyu Chang, Sijia Liu
How to Robustify Black-Box ML Models? A Zeroth-Order Optimization Perspective. CoRR (2022)
Lue Tao, Lei Feng, Jinfeng Yi, Songcan Chen
With False Friends Like These, Who Can Notice Mistakes? AAAI (2022)
Lijun Zhang, Guanghui Wang, Jinfeng Yi, Tianbao Yang
A Simple yet Universal Strategy for Online Convex Optimization. ICML (2022)
Yimeng Zhang, Yuguang Yao, Jinghan Jia, Jinfeng Yi, Mingyi Hong, Shiyu Chang, Sijia Liu
How to Robustify Black-Box ML Models? A Zeroth-Order Optimization Perspective. ICLR (2022)
Lijun Zhang, Wei Jiang, Jinfeng Yi, Tianbao Yang
Smoothed Online Convex Optimization Based on Discounted-Normal-Predictor. CoRR (2022)
Yunxiao Qin, Yuanhao Xiong, Jinfeng Yi, Cho-Jui Hsieh
Training Meta-Surrogate Model for Transferable Adversarial Attack. CoRR (2021)
Lue Tao, Lei Feng, Jinfeng Yi, Sheng-Jun Huang, Songcan Chen
Provable Defense Against Delusive Poisoning. CoRR (2021)
Sanshi Yu, Zhuoxuan Jiang, Dongdong Chen, Shanshan Feng, Dongsheng Li, Qi Liu, Jinfeng Yi
Leveraging Tripartite Interaction Information from Live Stream E-Commerce for Improving Product Recommendation. CoRR (2021)
Rulin Shao, Jinfeng Yi, Pin-Yu Chen, Cho-Jui Hsieh
How and When Adversarial Robustness Transfers in Knowledge Distillation? CoRR (2021)
Zhouxing Shi, Yihan Wang, Huan Zhang, Jinfeng Yi, Cho-Jui Hsieh
Fast Certified Robust Training with Short Warmup. NeurIPS (2021)
Zichen Ma, Zihan Lu, Yu Lu, Wenye Li, Jinfeng Yi, Shuguang Cui
Federated Two-stage Learning with Sign-based Voting. CoRR (2021)
Sanshi Yu, Zhuoxuan Jiang, Dongdong Chen, Shanshan Feng, Dongsheng Li, Qi Liu, Jinfeng Yi
Leveraging Tripartite Interaction Information from Live Stream E-Commerce for Improving Product Recommendation. KDD (2021)
Yongshun Gong, Jinfeng Yi, Dongdong Chen, Jian Zhang, Jiayu Zhou, Zhihua Zhou
Inferring the Importance of Product Appearance with Semi-supervised Multi-modal Enhancement: A Step Towards the Screenless Retailing. ACM Multimedia (2021)
Bo Li, Peng Qi, Bo Liu, Shuai Di, Jingen Liu, Jiquan Pei, Jinfeng Yi, Bowen Zhou
Trustworthy AI: From Principles to Practices. CoRR (2021)
Zichen Ma, Yu Lu, Zihan Lu, Wenye Li, Jinfeng Yi, Shuguang Cui
Towards Heterogeneous Clients with Elastic Federated Learning. CoRR (2021)
Zhouxing Shi, Yihan Wang, Huan Zhang, Jinfeng Yi, Cho-Jui Hsieh
Fast Certified Robust Training via Better Initialization and Shorter Warmup. CoRR (2021)
Xinwei Zhang, Xiangyi Chen, Mingyi Hong, Zhiwei Steven Wu, Jinfeng Yi
Understanding Clipping for Federated Learning: Convergence and Client-Level Differential Privacy. CoRR (2021)
Lue Tao, Lei Feng, Jinfeng Yi, Sheng-Jun Huang, Songcan Chen
Better Safe Than Sorry: Preventing Delusive Adversaries with Adversarial Training. NeurIPS (2021)
Rulin Shao, Zhouxing Shi, Jinfeng Yi, Pin-Yu Chen, Cho-Jui Hsieh
On the Adversarial Robustness of Visual Transformers. CoRR (2021)
Yisen Wang, Xingjun Ma, James Bailey, Jinfeng Yi, Bowen Zhou, Quanquan Gu
On the Convergence and Robustness of Adversarial Training. CoRR (2021)
Yunxiao Qin, Yuanhao Xiong, Jinfeng Yi, Cho-Jui Hsieh
Adversarial Attack across Datasets. CoRR (2021)
Jinze Wu, Qi Liu, Zhenya Huang, Yuting Ning, Hao Wang, Enhong Chen, Jinfeng Yi, Bowen Zhou
Hierarchical Personalized Federated Learning for User Modeling. WWW (2021)
Tianxin Wei, Fuli Feng, Jiawei Chen, Ziwei Wu, Jinfeng Yi, Xiangnan He
Model-Agnostic Counterfactual Reasoning for Eliminating Popularity Bias in Recommender System. KDD (2021)
Rulin Shao, Zhouxing Shi, Jinfeng Yi, Pin-Yu Chen, Cho-Jui Hsieh
Robust Text CAPTCHAs Using Adversarial Examples. CoRR (2021)
Lijun Zhang, Guanghui Wang, Jinfeng Yi, Tianbao Yang
A Simple yet Universal Strategy for Online Convex Optimization. CoRR (2021)
Zichen Ma, Yu Lu, Wenye Li, Jinfeng Yi, Shuguang Cui
PFedAtt: Attention-based Personalized Federated Learning on Heterogeneous Clients. ACML (2021)
Yongshun Gong, Zhibin Li, Jian Zhang, Wei Liu, Jinfeng Yi
Potential Passenger Flow Prediction: A Novel Study for Urban Transportation Development. AAAI (2020)
Jinghui Chen, Dongruo Zhou, Jinfeng Yi, Quanquan Gu
A Frank-Wolfe Framework for Efficient and Effective Adversarial Attacks. AAAI (2020)
Minhao Cheng, Jinfeng Yi, Pin-Yu Chen, Huan Zhang, Cho-Jui Hsieh
Seq2Sick: Evaluating the Robustness of Sequence-to-Sequence Models with Adversarial Examples. AAAI (2020)
Zhonghan Niu, Zhaoxi Chen, Linyi Li, Yubin Yang, Bo Li, Jinfeng Yi
On the Limitations of Denoising Strategies as Adversarial Defenses. CoRR (2020)
Lu Wang, Xuanqing Liu, Jinfeng Yi, Yuan Jiang, Cho-Jui Hsieh
Provably Robust Metric Learning. NeurIPS (2020)
Yisen Wang, Difan Zou, Jinfeng Yi, James Bailey, Xingjun Ma, Quanquan Gu
Improving Adversarial Robustness Requires Revisiting Misclassified Examples. ICLR (2020)
Tianxin Wei, Fuli Feng, Jiawei Chen, Chufeng Shi, Ziwei Wu, Jinfeng Yi, Xiangnan He
Model-Agnostic Counterfactual Reasoning for Eliminating Popularity Bias in Recommender System. CoRR (2020)
Lu Wang, Huan Zhang, Jinfeng Yi, Cho-Jui Hsieh, Yuan Jiang
Spanning attack: reinforce black-box attacks with unlabeled data. Mach. Learn. 109 (12) (2020)
Lu Wang, Huan Zhang, Jinfeng Yi, Cho-Jui Hsieh, Yuan Jiang
Spanning Attack: Reinforce Black-box Attacks with Unlabeled Data. CoRR (2020)
Lu Wang, Xuanqing Liu, Jinfeng Yi, Yuan Jiang, Cho-Jui Hsieh
Provably Robust Metric Learning. CoRR (2020)
Zhibin Li, Jian Zhang, Qiang Wu, Yongshun Gong, Jinfeng Yi, Christina Kirsch
Sample Adaptive Multiple Kernel Learning for Failure Prediction of Railway Points. KDD (2019)
Yongshun Gong, Zhibin Li, Jian Zhang, Wei Liu, Jinfeng Yi
Potential Passenger Flow Prediction: A Novel Study for Urban Transportation Development. CoRR (2019)
Yisen Wang, Xingjun Ma, James Bailey, Jinfeng Yi, Bowen Zhou, Quanquan Gu
On the Convergence and Robustness of Adversarial Training. ICML (2019)
Yifan Ding, Liqiang Wang, Huan Zhang, Jinfeng Yi, Deliang Fan, Boqing Gong
Defending Against Adversarial Attacks Using Random Forest. CVPR Workshops (2019)
Lu Wang, Xuanqing Liu, Jinfeng Yi, Zhi-Hua Zhou, Cho-Jui Hsieh
Evaluating the Robustness of Nearest Neighbor Classifiers: A Primal-Dual Perspective. CoRR (2019)
Yisen Wang, Xingjun Ma, Zaiyi Chen, Yuan Luo, Jinfeng Yi, James Bailey
Symmetric Cross Entropy for Robust Learning With Noisy Labels. ICCV (2019)
Xinlei Pan, Weiyao Wang, Xiaoshuai Zhang, Bo Li, Jinfeng Yi, Dawn Song
How You Act Tells a Lot: Privacy-Leakage Attack on Deep Reinforcement Learning. CoRR (2019)
Lan-Zhe Guo, Yu-Feng Li, Ming Li, Jinfeng Yi, Bowen Zhou, Zhi-Hua Zhou
Reliable Weakly Supervised Learning: Maximize Gain and Maintain Safeness. CoRR (2019)
Qi Lei, Jinfeng Yi, Roman Vaculín, Lingfei Wu, Inderjit S. Dhillon
Similarity Preserving Representation Learning for Time Series Clustering. IJCAI (2019)
Zaiyi Chen, Zhuoning Yuan, Jinfeng Yi, Bowen Zhou, Enhong Chen, Tianbao Yang
Universal Stagewise Learning for Non-Convex Problems with Convergence on Averaged Solutions. ICLR (Poster) (2019)
Zhibin Li, Jian Zhang, Qiang Wu, Yongshun Gong, Jinfeng Yi, Christina Kirsch
Sample Adaptive Multiple Kernel Learning for Failure Prediction of Railway Points. CoRR (2019)
Chun-Chen Tu, Pai-Shun Ting, Pin-Yu Chen, Sijia Liu, Huan Zhang, Jinfeng Yi, Cho-Jui Hsieh, Shin-Ming Cheng
AutoZOOM: Autoencoder-Based Zeroth Order Optimization Method for Attacking Black-Box Neural Networks. AAAI (2019)
Minhao Cheng, Thong Le, Pin-Yu Chen, Huan Zhang, Jinfeng Yi, Cho-Jui Hsieh
Query-Efficient Hard-label Black-box Attack: An Optimization-based Approach. ICLR (Poster) (2019)
Yifan Ding, Liqiang Wang, Huan Zhang, Jinfeng Yi, Deliang Fan, Boqing Gong
Defending Against Adversarial Attacks Using Random Forests. CoRR (2019)
Pengcheng Li, Jinfeng Yi, Bowen Zhou, Lijun Zhang
Improving the Robustness of Deep Neural Networks via Adversarial Training with Triplet Loss. IJCAI (2019)
Xingyu Cai, Tingyang Xu, Jinfeng Yi, Junzhou Huang, Sanguthevar Rajasekaran
DTWNet: a Dynamic Time Warping Network. NeurIPS (2019)
Yali Du, Meng Fang, Jinfeng Yi, Chang Xu, Jun Cheng, Dacheng Tao
Enhancing the Robustness of Neural Collaborative Filtering Systems Under Malicious Attacks. IEEE Trans. Multim. 21 (3) (2019)
Pengcheng Li, Jinfeng Yi, Bowen Zhou, Lijun Zhang
Improving the Robustness of Deep Neural Networks via Adversarial Training with Triplet Loss. CoRR (2019)
Yisen Wang, Xingjun Ma, Zaiyi Chen, Yuan Luo, Jinfeng Yi, James Bailey
Symmetric Cross Entropy for Robust Learning with Noisy Labels. CoRR (2019)
Chaowei Xiao, Xinlei Pan, Warren He, Jian Peng, Mingjie Sun, Jinfeng Yi, Mingyan Liu, Bo Li, Dawn Song
Characterizing Attacks on Deep Reinforcement Learning. CoRR (2019)
Chaowei Xiao, Ruizhi Deng, Bo Li, Taesung Lee, Benjamin Edwards, Jinfeng Yi, Dawn Song, Mingyan Liu, Ian M. Molloy
AdvIT: Adversarial Frames Identifier Based on Temporal Consistency in Videos. ICCV (2019)
Dongdong Chen, Yisen Wang, Jinfeng Yi, Zaiyi Chen, Zhi-Hua Zhou
Joint Semantic Domain Alignment and Target Classifier Learning for Unsupervised Domain Adaptation. CoRR (2019)
Xingyu Cai, Jinfeng Yi, Fan Zhang, Sanguthevar Rajasekaran
Adversarial Structured Neural Network Pruning. CIKM (2019)
Xinlei Pan, Weiyao Wang, Xiaoshuai Zhang, Bo Li, Jinfeng Yi, Dawn Song
How You Act Tells a Lot: Privacy-Leaking Attack on Deep Reinforcement Learning. AAMAS (2019)
Jinfeng Yi, Qi Lei, Wesley M. Gifford, Ji Liu, Junchi Yan, Bowen Zhou
Fast Unsupervised Location Category Inference from Highly Inaccurate Mobility Data. SDM (2019)
Pengcheng Li, Jinfeng Yi, Lijun Zhang
Query-Efficient Black-Box Attack by Active Learning. CoRR (2018)
Dong Su, Huan Zhang, Hongge Chen, Jinfeng Yi, Pin-Yu Chen, Yupeng Gao
Is Robustness the Cost of Accuracy? - A Comprehensive Study on the Robustness of 18 Deep Image Classification Models. CoRR (2018)
Yali Du, Meng Fang, Jinfeng Yi, Jun Cheng, Dacheng Tao
Towards Query Efficient Black-box Attacks: An Input-free Perspective. CoRR (2018)
Minhao Cheng, Thong Le, Pin-Yu Chen, Jinfeng Yi, Huan Zhang, Cho-Jui Hsieh
Query-Efficient Hard-label Black-box Attack: An Optimization-based Approach. CoRR (2018)
Adnan Siraj Rakin, Jinfeng Yi, Boqing Gong, Deliang Fan
Defend Deep Neural Networks Against Adversarial Examples via Fixed andDynamic Quantized Activation Functions. CoRR (2018)
Yali Du, Meng Fang, Jinfeng Yi, Jun Cheng, Dacheng Tao
Towards Query Efficient Black-box Attacks: An Input-free Perspective. AISec@CCS (2018)
Pin-Yu Chen, Yash Sharma, Huan Zhang, Jinfeng Yi, Cho-Jui Hsieh
EAD: Elastic-Net Attacks to Deep Neural Networks via Adversarial Examples. AAAI (2018)
Mengying Sun, Fengyi Tang, Jinfeng Yi, Fei Wang, Jiayu Zhou
Identify Susceptible Locations in Medical Records via Adversarial Attacks on Deep Predictive Models. CoRR (2018)
Lingfei Wu, Ian En-Hsu Yen, Jinfeng Yi, Fangli Xu, Qi Lei, Michael Witbrock
Random Warping Series: A Random Features Method for Time-Series Embedding. AISTATS (2018)
Tsui-Wei Weng, Huan Zhang, Pin-Yu Chen, Jinfeng Yi, Dong Su, Yupeng Gao, Cho-Jui Hsieh, Luca Daniel
Evaluating the Robustness of Neural Networks: An Extreme Value Theory Approach. ICLR (Poster) (2018)
Yuanyu Wan, Jinfeng Yi, Lijun Zhang
Matrix Completion from Non-Uniformly Sampled Entries. CoRR (2018)
Pengcheng Li, Jinfeng Yi, Lijun Zhang
Query-Efficient Black-Box Attack by Active Learning. ICDM (2018)
Jinghui Chen, Jinfeng Yi, Quanquan Gu
A Frank-Wolfe Framework for Efficient and Effective Adversarial Attacks. CoRR (2018)
Hongge Chen, Huan Zhang, Pin-Yu Chen, Jinfeng Yi, Cho-Jui Hsieh
Attacking Visual Language Grounding with Adversarial Examples: A Case Study on Neural Image Captioning. ACL (1) (2018)
Jinfeng Yi, Qi Lei, Junchi Yan, Wei Sun
Session Expert: a Lightweight Conference Session Recommender System. IEEE BigData (2018)
Mingrui Liu, Zhe Li, Xiaoyu Wang, Jinfeng Yi, Tianbao Yang
Adaptive Negative Curvature Descent with Applications in Non-convex Optimization. NeurIPS (2018)
Dong Su, Huan Zhang, Hongge Chen, Jinfeng Yi, Pin-Yu Chen, Yupeng Gao
Is Robustness the Cost of Accuracy? - A Comprehensive Study on the Robustness of 18 Deep Image Classification Models. ECCV (12) (2018)
Minhao Cheng, Jinfeng Yi, Huan Zhang, Pin-Yu Chen, Cho-Jui Hsieh
Seq2Sick: Evaluating the Robustness of Sequence-to-Sequence Models with Adversarial Examples. CoRR (2018)
Tsui-Wei Weng, Huan Zhang, Pin-Yu Chen, Jinfeng Yi, Dong Su, Yupeng Gao, Cho-Jui Hsieh, Luca Daniel
Evaluating the Robustness of Neural Networks: An Extreme Value Theory Approach. CoRR (2018)
Zhao Kang, Xiao Lu, Jinfeng Yi, Zenglin Xu
Self-weighted Multiple Kernel Learning for Graph-based Clustering and Semi-supervised Classification. IJCAI (2018)
Zhao Kang, Xiao Lu, Jinfeng Yi, Zenglin Xu
Self-weighted Multiple Kernel Learning for Graph-based Clustering and Semi-supervised Classification. CoRR (2018)
Mo Yu, Xiaoxiao Guo, Jinfeng Yi, Shiyu Chang, Saloni Potdar, Yu Cheng, Gerald Tesauro, Haoyu Wang, Bowen Zhou
Diverse Few-Shot Text Classification with Multiple Metrics. CoRR (2018)
Mo Yu, Xiaoxiao Guo, Jinfeng Yi, Shiyu Chang, Saloni Potdar, Yu Cheng, Gerald Tesauro, Haoyu Wang, Bowen Zhou
Diverse Few-Shot Text Classification with Multiple Metrics. NAACL-HLT (2018)
Lingfei Wu, Ian En-Hsu Yen, Jinfeng Yi, Fangli Xu, Qi Lei, Michael Witbrock
Random Warping Series: A Random Features Method for Time-Series Embedding. CoRR (2018)
Chun-Chen Tu, Pai-Shun Ting, Pin-Yu Chen, Sijia Liu, Huan Zhang, Jinfeng Yi, Cho-Jui Hsieh, Shin-Ming Cheng
AutoZOOM: Autoencoder-based Zeroth Order Optimization Method for Attacking Black-box Neural Networks. CoRR (2018)

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Publication Activity (10 Years)

Top Topics

Top Venues

Jinfeng Yi