default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDJinfeng Yi
易津锋
Person information
- unicode name: 易津锋
- affiliation: JD.com AI Research, Beijing, China
Other persons with a similar name
SPARQL queries 
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2024
[i57]Yuhan Quan, Huan Zhao, Jinfeng Yi, Yuqiang Chen:
Self-supervised Graph Neural Network for Mechanical CAD Retrieval. CoRR abs/2406.08863 (2024)- 2023
- [j6]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): 177:1-177:46 (2023) - [j5]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): 46:1-46:33 (2023) - [c68]Yunxiao Qin, Yuanhao Xiong, Jinfeng Yi, Cho-Jui Hsieh:
Training Meta-Surrogate Model for Transferable Adversarial Attack. AAAI 2023: 9516-9524 - [c67]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: 32304-32330 - [c66]Bo Xue, Yimu Wang, Yuanyu Wan, Jinfeng Yi, Lijun Zhang:
Efficient Algorithms for Generalized Linear Bandits with Heavy-tailed Rewards. NeurIPS 2023 - [c65]Yutian Gou, Jinfeng Yi, Lijun Zhang:
Stochastic Graphical Bandits with Heavy-Tailed Rewards. UAI 2023: 734-744 - [i56]Bo Xue, Yimu Wang, Yuanyu Wan, Jinfeng Yi, Lijun Zhang:
Efficient Algorithms for Generalized Linear Bandits with Heavy-tailed Rewards. CoRR abs/2310.18701 (2023) - 2022
- [j4]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) - [c64]Lue Tao, Lei Feng, Jinfeng Yi, Songcan Chen:
With False Friends Like These, Who Can Notice Mistakes? AAAI 2022: 8458-8466 - [c63]Rulin Shao, Zhouxing Shi, Jinfeng Yi, Pin-Yu Chen, Cho-Jui Hsieh:
Robust Text CAPTCHAs Using Adversarial Examples. IEEE Big Data 2022: 1495-1504 - [c62]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 - [c61]Xinwei Zhang, Xiangyi Chen, Mingyi Hong, Steven Wu, Jinfeng Yi:
Understanding Clipping for Federated Learning: Convergence and Client-Level Differential Privacy. ICML 2022: 26048-26067 - [c60]Lijun Zhang, Guanghui Wang, Jinfeng Yi, Tianbao Yang:
A Simple yet Universal Strategy for Online Convex Optimization. ICML 2022: 26605-26623 - [c59]Lue Tao, Lei Feng, Hongxin Wei, Jinfeng Yi, Sheng-Jun Huang, Songcan Chen:
Can Adversarial Training Be Manipulated By Non-Robust Features? NeurIPS 2022 - [c58]Lijun Zhang, Wei Jiang, Jinfeng Yi, Tianbao Yang:
Smoothed Online Convex Optimization Based on Discounted-Normal-Predictor. NeurIPS 2022 - [c57]Yingchun Jian, Jinfeng Yi, Lijun Zhang:
Adaptive Feature Generation for Online Continual Learning from Imbalanced Data. PAKDD (1) 2022: 276-289 - [i55]Lue Tao, Lei Feng, Hongxin Wei, Jinfeng Yi, Sheng-Jun Huang, Songcan Chen:
Can Adversarial Training Be Manipulated By Non-Robust Features? CoRR abs/2201.13329 (2022) - [i54]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 abs/2203.14195 (2022) - [i53]Lijun Zhang, Wei Jiang, Jinfeng Yi, Tianbao Yang:
Smoothed Online Convex Optimization Based on Discounted-Normal-Predictor. CoRR abs/2205.00741 (2022) - 2021
- [c56]Zichen Ma, Yu Lu, Wenye Li, Jinfeng Yi, Shuguang Cui:
PFedAtt: Attention-based Personalized Federated Learning on Heterogeneous Clients. ACML 2021: 1253-1268 - [c55]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: 1791-1800 - [c54]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: 3886-3894 - [c53]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: 1120-1128 - [c52]Lue Tao, Lei Feng, Jinfeng Yi, Sheng-Jun Huang, Songcan Chen:
Better Safe Than Sorry: Preventing Delusive Adversaries with Adversarial Training. NeurIPS 2021: 16209-16225 - [c51]Zhouxing Shi, Yihan Wang, Huan Zhang, Jinfeng Yi, Cho-Jui Hsieh:
Fast Certified Robust Training with Short Warmup. NeurIPS 2021: 18335-18349 - [c50]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: 957-968 - [i52]Rulin Shao, Zhouxing Shi, Jinfeng Yi, Pin-Yu Chen, Cho-Jui Hsieh:
Robust Text CAPTCHAs Using Adversarial Examples. CoRR abs/2101.02483 (2021) - [i51]Lue Tao, Lei Feng, Jinfeng Yi, Sheng-Jun Huang, Songcan Chen:
Provable Defense Against Delusive Poisoning. CoRR abs/2102.04716 (2021) - [i50]Rulin Shao, Zhouxing Shi, Jinfeng Yi, Pin-Yu Chen, Cho-Jui Hsieh:
On the Adversarial Robustness of Visual Transformers. CoRR abs/2103.15670 (2021) - [i49]Zhouxing Shi, Yihan Wang, Huan Zhang, Jinfeng Yi, Cho-Jui Hsieh:
Fast Certified Robust Training via Better Initialization and Shorter Warmup. CoRR abs/2103.17268 (2021) - [i48]Lijun Zhang, Guanghui Wang, Jinfeng Yi, Tianbao Yang:
A Simple yet Universal Strategy for Online Convex Optimization. CoRR abs/2105.03681 (2021) - [i47]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 abs/2106.03415 (2021) - [i46]Zichen Ma, Yu Lu, Zihan Lu, Wenye Li, Jinfeng Yi, Shuguang Cui:
Towards Heterogeneous Clients with Elastic Federated Learning. CoRR abs/2106.09433 (2021) - [i45]Xinwei Zhang, Xiangyi Chen, Mingyi Hong, Zhiwei Steven Wu, Jinfeng Yi:
Understanding Clipping for Federated Learning: Convergence and Client-Level Differential Privacy. CoRR abs/2106.13673 (2021) - [i44]Yunxiao Qin, Yuanhao Xiong, Jinfeng Yi, Cho-Jui Hsieh:
Training Meta-Surrogate Model for Transferable Adversarial Attack. CoRR abs/2109.01983 (2021) - [i43]Bo Li, Peng Qi, Bo Liu, Shuai Di, Jingen Liu, Jiquan Pei, Jinfeng Yi, Bowen Zhou:
Trustworthy AI: From Principles to Practices. CoRR abs/2110.01167 (2021) - [i42]Yunxiao Qin, Yuanhao Xiong, Jinfeng Yi, Cho-Jui Hsieh:
Adversarial Attack across Datasets. CoRR abs/2110.07718 (2021) - [i41]Rulin Shao, Jinfeng Yi, Pin-Yu Chen, Cho-Jui Hsieh:
How and When Adversarial Robustness Transfers in Knowledge Distillation? CoRR abs/2110.12072 (2021) - [i40]Zichen Ma, Zihan Lu, Yu Lu, Wenye Li, Jinfeng Yi, Shuguang Cui:
Federated Two-stage Learning with Sign-based Voting. CoRR abs/2112.05687 (2021) - [i39]Yisen Wang, Xingjun Ma, James Bailey, Jinfeng Yi, Bowen Zhou, Quanquan Gu:
On the Convergence and Robustness of Adversarial Training. CoRR abs/2112.08304 (2021) - 2020
- [j3]Lu Wang, Huan Zhang, Jinfeng Yi, Cho-Jui Hsieh, Yuan Jiang:
Spanning attack: reinforce black-box attacks with unlabeled data. Mach. Learn. 109(12): 2349-2368 (2020) - [c49]Jinghui Chen, Dongruo Zhou, Jinfeng Yi, Quanquan Gu:
A Frank-Wolfe Framework for Efficient and Effective Adversarial Attacks. AAAI 2020: 3486-3494 - [c48]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: 3601-3608 - [c47]Yongshun Gong, Zhibin Li, Jian Zhang, Wei Liu, Jinfeng Yi:
Potential Passenger Flow Prediction: A Novel Study for Urban Transportation Development. AAAI 2020: 4020-4027 - [c46]Yisen Wang, Difan Zou, Jinfeng Yi, James Bailey, Xingjun Ma, Quanquan Gu:
Improving Adversarial Robustness Requires Revisiting Misclassified Examples. ICLR 2020 - [c45]Lu Wang, Xuanqing Liu, Jinfeng Yi, Yuan Jiang, Cho-Jui Hsieh:
Provably Robust Metric Learning. NeurIPS 2020 - [i38]Lu Wang, Huan Zhang, Jinfeng Yi, Cho-Jui Hsieh, Yuan Jiang:
Spanning Attack: Reinforce Black-box Attacks with Unlabeled Data. CoRR abs/2005.04871 (2020) - [i37]Lu Wang, Xuanqing Liu, Jinfeng Yi, Yuan Jiang, Cho-Jui Hsieh:
Provably Robust Metric Learning. CoRR abs/2006.07024 (2020) - [i36]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 abs/2010.15363 (2020) - [i35]Zhonghan Niu, Zhaoxi Chen, Linyi Li, Yubin Yang, Bo Li, Jinfeng Yi:
On the Limitations of Denoising Strategies as Adversarial Defenses. CoRR abs/2012.09384 (2020)
2010 – 2019
- 2019
- [j2]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): 555-565 (2019) - [c44]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: 742-749 - [c43]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: 368-376 - [c42]Xingyu Cai, Jinfeng Yi, Fan Zhang, Sanguthevar Rajasekaran:
Adversarial Structured Neural Network Pruning. CIKM 2019: 2433-2436 - [c41]Yifan Ding, Liqiang Wang, Huan Zhang, Jinfeng Yi, Deliang Fan, Boqing Gong:
Defending Against Adversarial Attacks Using Random Forest. CVPR Workshops 2019: 105-114 - [c40]Yisen Wang, Xingjun Ma, Zaiyi Chen, Yuan Luo, Jinfeng Yi, James Bailey:
Symmetric Cross Entropy for Robust Learning With Noisy Labels. ICCV 2019: 322-330 - [c39]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: 3967-3976 - [c38]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 - [c37]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 - [c36]Yisen Wang, Xingjun Ma, James Bailey, Jinfeng Yi, Bowen Zhou, Quanquan Gu:
On the Convergence and Robustness of Adversarial Training. ICML 2019: 6586-6595 - [c35]Qi Lei, Jinfeng Yi, Roman Vaculín, Lingfei Wu, Inderjit S. Dhillon:
Similarity Preserving Representation Learning for Time Series Clustering. IJCAI 2019: 2845-2851 - [c34]Pengcheng Li, Jinfeng Yi, Bowen Zhou, Lijun Zhang:
Improving the Robustness of Deep Neural Networks via Adversarial Training with Triplet Loss. IJCAI 2019: 2909-2915 - [c33]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: 2848-2856 - [c32]Xingyu Cai, Tingyang Xu, Jinfeng Yi, Junzhou Huang, Sanguthevar Rajasekaran:
DTWNet: a Dynamic Time Warping Network. NeurIPS 2019: 11636-11646 - [c31]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: 55-63 - [i34]Lan-Zhe Guo, Yufeng Li, Ming Li, Jinfeng Yi, Bowen Zhou, Zhi-Hua Zhou:
Reliable Weakly Supervised Learning: Maximize Gain and Maintain Safeness. CoRR abs/1904.09743 (2019) - [i33]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 abs/1904.11082 (2019) - [i32]Pengcheng Li, Jinfeng Yi, Bowen Zhou, Lijun Zhang:
Improving the Robustness of Deep Neural Networks via Adversarial Training with Triplet Loss. CoRR abs/1905.11713 (2019) - [i31]Lu Wang, Xuanqing Liu, Jinfeng Yi, Zhi-Hua Zhou, Cho-Jui Hsieh:
Evaluating the Robustness of Nearest Neighbor Classifiers: A Primal-Dual Perspective. CoRR abs/1906.03972 (2019) - [i30]Dongdong Chen, Yisen Wang, Jinfeng Yi, Zaiyi Chen, Zhi-Hua Zhou:
Joint Semantic Domain Alignment and Target Classifier Learning for Unsupervised Domain Adaptation. CoRR abs/1906.04053 (2019) - [i29]Yifan Ding, Liqiang Wang, Huan Zhang, Jinfeng Yi, Deliang Fan, Boqing Gong:
Defending Against Adversarial Attacks Using Random Forests. CoRR abs/1906.06765 (2019) - [i28]Zhibin Li, Jian Zhang, Qiang Wu, Yongshun Gong, Jinfeng Yi, Christina Kirsch:
Sample Adaptive Multiple Kernel Learning for Failure Prediction of Railway Points. CoRR abs/1907.01162 (2019) - [i27]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 abs/1907.09470 (2019) - [i26]Yisen Wang, Xingjun Ma, Zaiyi Chen, Yuan Luo, Jinfeng Yi, James Bailey:
Symmetric Cross Entropy for Robust Learning with Noisy Labels. CoRR abs/1908.06112 (2019) - [i25]Yongshun Gong, Zhibin Li, Jian Zhang, Wei Liu, Jinfeng Yi:
Potential Passenger Flow Prediction: A Novel Study for Urban Transportation Development. CoRR abs/1912.03440 (2019) - 2018
- [c30]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: 10-17 - [c29]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: 2587-2597 - [c28]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: 793-802 - [c27]Jinfeng Yi, Qi Lei, Junchi Yan, Wei Sun:
Session Expert: a Lightweight Conference Session Recommender System. IEEE BigData 2018: 1677-1682 - [c26]Yali Du, Meng Fang, Jinfeng Yi, Jun Cheng, Dacheng Tao:
Towards Query Efficient Black-box Attacks: An Input-free Perspective. AISec@CCS 2018: 13-24 - [c25]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: 644-661 - [c24]Pengcheng Li, Jinfeng Yi, Lijun Zhang:
Query-Efficient Black-Box Attack by Active Learning. ICDM 2018: 1200-1205 - [c23]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 - [c22]Zhao Kang, Xiao Lu, Jinfeng Yi, Zenglin Xu:
Self-weighted Multiple Kernel Learning for Graph-based Clustering and Semi-supervised Classification. IJCAI 2018: 2312-2318 - [c21]Mengying Sun, Fengyi Tang, Jinfeng Yi, Fei Wang, Jiayu Zhou:
Identify Susceptible Locations in Medical Records via Adversarial Attacks on Deep Predictive Models. KDD 2018: 793-801 - [c20]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: 1206-1215 - [c19]Mingrui Liu, Zhe Li, Xiaoyu Wang, Jinfeng Yi, Tianbao Yang:
Adaptive Negative Curvature Descent with Applications in Non-convex Optimization. NeurIPS 2018: 4858-4867 - [i24]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 abs/1801.10578 (2018) - [i23]Mengying Sun, Fengyi Tang, Jinfeng Yi, Fei Wang, Jiayu Zhou:
Identify Susceptible Locations in Medical Records via Adversarial Attacks on Deep Predictive Models. CoRR abs/1802.04822 (2018) - [i22]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 abs/1803.01128 (2018) - [i21]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 abs/1805.07513 (2018) - [i20]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 abs/1805.11770 (2018) - [i19]Zhao Kang, Xiao Lu, Jinfeng Yi, Zenglin Xu:
Self-weighted Multiple Kernel Learning for Graph-based Clustering and Semi-supervised Classification. CoRR abs/1806.07697 (2018) - [i18]Yuanyu Wan, Jinfeng Yi, Lijun Zhang:
Matrix Completion from Non-Uniformly Sampled Entries. CoRR abs/1806.10308 (2018) - [i17]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 abs/1807.04457 (2018) - [i16]Adnan Siraj Rakin, Jinfeng Yi, Boqing Gong, Deliang Fan:
Defend Deep Neural Networks Against Adversarial Examples via Fixed andDynamic Quantized Activation Functions. CoRR abs/1807.06714 (2018) - [i15]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 abs/1808.01688 (2018) - [i14]Yali Du, Meng Fang, Jinfeng Yi, Jun Cheng, Dacheng Tao:
Towards Query Efficient Black-box Attacks: An Input-free Perspective. CoRR abs/1809.02918 (2018) - [i13]Pengcheng Li, Jinfeng Yi, Lijun Zhang:
Query-Efficient Black-Box Attack by Active Learning. CoRR abs/1809.04913 (2018) - [i12]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 abs/1809.05259 (2018) - [i11]Jinghui Chen, Jinfeng Yi, Quanquan Gu:
A Frank-Wolfe Framework for Efficient and Effective Adversarial Attacks. CoRR abs/1811.10828 (2018) - 2017
- [c18]Pin-Yu Chen, Huan Zhang, Yash Sharma, Jinfeng Yi, Cho-Jui Hsieh:
ZOO: Zeroth Order Optimization Based Black-box Attacks to Deep Neural Networks without Training Substitute Models. AISec@CCS 2017: 15-26 - [c17]Lijun Zhang, Tianbao Yang, Jinfeng Yi, Rong Jin, Zhi-Hua Zhou:
Improved Dynamic Regret for Non-degenerate Functions. NIPS 2017: 732-741 - [c16]Jinfeng Yi, Cho-Jui Hsieh, Kush R. Varshney, Lijun Zhang, Yao Li:
Scalable Demand-Aware Recommendation. NIPS 2017: 2412-2421 - [i10]Qi Lei, Jinfeng Yi, Roman Vaculín, Lingfei Wu, Inderjit S. Dhillon:
Similarity Preserving Representation Learning for Time Series Analysis. CoRR abs/1702.03584 (2017) - [i9]Jinfeng Yi, Cho-Jui Hsieh, Kush R. Varshney, Lijun Zhang, Yao Li:
Positive-Unlabeled Demand-Aware Recommendation. CoRR abs/1702.06347 (2017) - [i8]Jinfeng Yi, Qi Lei, Wesley M. Gifford, Ji Liu:
Negative-Unlabeled Tensor Factorization for Location Category Inference from Inaccurate Mobility Data. CoRR abs/1702.06362 (2017) - [i7]Pin-Yu Chen, Huan Zhang, Yash Sharma, Jinfeng Yi, Cho-Jui Hsieh:
ZOO: Zeroth Order Optimization based Black-box Attacks to Deep Neural Networks without Training Substitute Models. CoRR abs/1708.03999 (2017) - [i6]Mo Yu, Xiaoxiao Guo, Jinfeng Yi, Shiyu Chang, Saloni Potdar, Gerald Tesauro, Haoyu Wang, Bowen Zhou:
Robust Task Clustering for Deep Many-Task Learning. CoRR abs/1708.07918 (2017) - [i5]Pin-Yu Chen, Yash Sharma, Huan Zhang, Jinfeng Yi, Cho-Jui Hsieh:
EAD: Elastic-Net Attacks to Deep Neural Networks via Adversarial Examples. CoRR abs/1709.04114 (2017) - [i4]Hongge Chen, Huan Zhang, Pin-Yu Chen, Jinfeng Yi, Cho-Jui Hsieh:
Show-and-Fool: Crafting Adversarial Examples for Neural Image Captioning. CoRR abs/1712.02051 (2017) - 2016
- [c15]Lijun Zhang, Tianbao Yang, Jinfeng Yi, Rong Jin, Zhi-Hua Zhou:
Stochastic Optimization for Kernel PCA. AAAI 2016: 2315-2322 - [c14]Raya Horesh, Kush R. Varshney, Jinfeng Yi:
Information retrieval, fusion, completion, and clustering for employee expertise estimation. IEEE BigData 2016: 1385-1393 - [c13]Tianbao Yang, Lijun Zhang, Rong Jin, Jinfeng Yi:
Tracking Slowly Moving Clairvoyant: Optimal Dynamic Regret of Online Learning with True and Noisy Gradient. ICML 2016: 449-457 - [i3]Tianbao Yang, Lijun Zhang, Rong Jin, Jinfeng Yi:
Tracking Slowly Moving Clairvoyant: Optimal Dynamic Regret of Online Learning with True and Noisy Gradient. CoRR abs/1605.04638 (2016) - [i2]Lijun Zhang, Tianbao Yang, Jinfeng Yi, Rong Jin, Zhi-Hua Zhou:
Improved dynamic regret for non-degeneracy functions. CoRR abs/1608.03933 (2016) - 2015
- [j1]Qi Qian, Rong Jin, Jinfeng Yi, Lijun Zhang, Shenghuo Zhu:
Efficient distance metric learning by adaptive sampling and mini-batch stochastic gradient descent (SGD). Mach. Learn. 99(3): 353-372 (2015) - [c12]Jinfeng Yi, Lijun Zhang, Tianbao Yang, Wei Liu, Jun Wang:
An Efficient Semi-Supervised Clustering Algorithm with Sequential Constraints. KDD 2015: 1405-1414 - 2014
- [c11]Jinfeng Yi, Jun Wang, Rong Jin:
Privacy and Regression Model Preserved Learning. AAAI 2014: 1341-1347 - [c10]Jinfeng Yi, Lijun Zhang, Jun Wang, Rong Jin, Anil K. Jain:
A Single-Pass Algorithm for Efficiently Recovering Sparse Cluster Centers of High-dimensional Data. ICML 2014: 658-666 - [c9]Lijun Zhang, Jinfeng Yi, Rong Jin:
Efficient Algorithms for Robust One-bit Compressive Sensing. ICML 2014: 820-828 - 2013
- [c8]Jinfeng Yi, Rong Jin, Shaili Jain, Anil K. Jain:
Inferring Users' Preferences from Crowdsourced Pairwise Comparisons: A Matrix Completion Approach. HCOMP 2013: 207-215 - [c7]Lijun Zhang, Jinfeng Yi, Rong Jin, Ming Lin, Xiaofei He:
Online Kernel Learning with a Near Optimal Sparsity Bound. ICML (3) 2013: 621-629 - [c6]Jinfeng Yi, Lijun Zhang, Rong Jin, Qi Qian, Anil K. Jain:
Semi-supervised Clustering by Input Pattern Assisted Pairwise Similarity Matrix Completion. ICML (3) 2013: 1400-1408 - [i1]Qi Qian, Rong Jin, Jinfeng Yi, Lijun Zhang, Shenghuo Zhu:
Efficient Distance Metric Learning by Adaptive Sampling and Mini-Batch Stochastic Gradient Descent (SGD). CoRR abs/1304.1192 (2013) - 2012
- [c5]Tianbao Yang, Mehrdad Mahdavi, Rong Jin, Jinfeng Yi, Steven C. H. Hoi:
Online Kernel Selection: Algorithms and Evaluations. AAAI 2012: 1197-1203 - [c4]Jinfeng Yi, Rong Jin, Anil K. Jain, Shaili Jain:
Crowdclustering with Sparse Pairwise Labels: A Matrix Completion Approach. HCOMP@AAAI 2012 - [c3]Jinfeng Yi, Tianbao Yang, Rong Jin, Anil K. Jain, Mehrdad Mahdavi:
Robust Ensemble Clustering by Matrix Completion. ICDM 2012: 1176-1181 - [c2]Mehrdad Mahdavi, Tianbao Yang, Rong Jin, Shenghuo Zhu, Jinfeng Yi:
Stochastic Gradient Descent with Only One Projection. NIPS 2012: 503-511 - [c1]Jinfeng Yi, Rong Jin, Anil K. Jain, Shaili Jain, Tianbao Yang:
Semi-Crowdsourced Clustering: Generalizing Crowd Labeling by Robust Distance Metric Learning. NIPS 2012: 1781-1789
Coauthor Index
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2025-01-16 22:05 CET by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
