Online Kernel Selection: Algorithms and Evaluations. - Tianbao Yang; Mehrdad Mahdavi; Rong Jin 001; Jinfeng Yi; Steven C. H. Hoi (AAAI, 2012)

Crowdclustering with Sparse Pairwise Labels: A Matrix Completion Approach. - Jinfeng Yi; Rong Jin 001; Anil K. Jain 001; Shaili Jain (HCOMP@AAAI, 2012)

Robust Ensemble Clustering by Matrix Completion. - Jinfeng Yi; Tianbao Yang; Rong Jin 001; Anil K. Jain 001; Mehrdad Mahdavi (ICDM, 2012)

Stochastic Gradient Descent with Only One Projection. - Mehrdad Mahdavi; Tianbao Yang; Rong Jin 001; Shenghuo Zhu; Jinfeng Yi (NIPS, 2012)

Semi-Crowdsourced Clustering: Generalizing Crowd Labeling by Robust Distance Metric Learning. - Jinfeng Yi; Rong Jin 001; Anil K. Jain 001; Shaili Jain; Tianbao Yang (NIPS, 2012)

Inferring Users' Preferences from Crowdsourced Pairwise Comparisons: A Matrix Completion Approach. - Jinfeng Yi; Rong Jin 001; Shaili Jain; Anil K. Jain 001 (HCOMP, 2013)

Semi-supervised Clustering by Input Pattern Assisted Pairwise Similarity Matrix Completion. - Jinfeng Yi; Lijun Zhang 005; Rong Jin 001; Qi Qian 001; Anil K. Jain 001 (ICML (3), 2013)

Online Kernel Learning with a Near Optimal Sparsity Bound. - Lijun Zhang 005; Jinfeng Yi; Rong Jin 001; Ming Lin 002; Xiaofei He 001 (ICML (3), 2013)

Privacy and Regression Model Preserved Learning. - Jinfeng Yi; Jun Wang 006; Rong Jin 001 (AAAI, 2014)

Efficient Algorithms for Robust One-bit Compressive Sensing. - Lijun Zhang 005; Jinfeng Yi; Rong Jin 001 (ICML, 2014)

A Single-Pass Algorithm for Efficiently Recovering Sparse Cluster Centers of High-dimensional Data. - Jinfeng Yi; Lijun Zhang 005; Jun Wang 006; Rong Jin 001; Anil K. Jain 001 (ICML, 2014)

An Efficient Semi-Supervised Clustering Algorithm with Sequential Constraints. - Jinfeng Yi; Lijun Zhang 005; Tianbao Yang; Wei Liu 005; Jun Wang 006 (KDD, 2015)

Efficient distance metric learning by adaptive sampling and mini-batch stochastic gradient descent (SGD). - Qi Qian 001; Rong Jin 001; Jinfeng Yi; Lijun Zhang 005; Shenghuo Zhu (Mach. Learn., 2015)

Stochastic Optimization for Kernel PCA. - Lijun Zhang 005; Tianbao Yang; Jinfeng Yi; Rong Jin 001; Zhi-Hua Zhou (AAAI, 2016)

Information retrieval, fusion, completion, and clustering for employee expertise estimation. - Raya Horesh; Kush R. Varshney; Jinfeng Yi (IEEE BigData, 2016)

Tracking Slowly Moving Clairvoyant: Optimal Dynamic Regret of Online Learning with True and Noisy Gradient. - Tianbao Yang; Lijun Zhang 005; Rong Jin 001; Jinfeng Yi (ICML, 2016)

Improved dynamic regret for non-degeneracy functions. - Lijun Zhang 005; Tianbao Yang; Jinfeng Yi; Rong Jin 001; Zhi-Hua Zhou (CoRR, 2016)

ZOO: Zeroth Order Optimization Based Black-box Attacks to Deep Neural Networks without Training Substitute Models. - Pin-Yu Chen; Huan Zhang 001; Yash Sharma 001; Jinfeng Yi; Cho-Jui Hsieh (AISec@CCS, 2017)

Improved Dynamic Regret for Non-degenerate Functions. - Lijun Zhang 005; Tianbao Yang; Jinfeng Yi; Rong Jin 001; Zhi-Hua Zhou (NIPS, 2017)

Scalable Demand-Aware Recommendation. - Jinfeng Yi; Cho-Jui Hsieh; Kush R. Varshney; Lijun Zhang 005; Yao Li 015 (NIPS, 2017)

Similarity Preserving Representation Learning for Time Series Analysis. - Qi Lei; Jinfeng Yi; Roman Vaculín; Lingfei Wu 001; Inderjit S. Dhillon (CoRR, 2017)

Positive-Unlabeled Demand-Aware Recommendation. - Jinfeng Yi; Cho-Jui Hsieh; Kush R. Varshney; Lijun Zhang 005; Yao Li 015 (CoRR, 2017)

Negative-Unlabeled Tensor Factorization for Location Category Inference from Inaccurate Mobility Data. - Jinfeng Yi; Qi Lei; Wesley M. Gifford; Ji Liu (CoRR, 2017)

Robust Task Clustering for Deep Many-Task Learning. - Mo Yu; Xiaoxiao Guo; Jinfeng Yi; Shiyu Chang; Saloni Potdar; Gerald Tesauro; Haoyu Wang 002; Bowen Zhou (CoRR, 2017)

Show-and-Fool: Crafting Adversarial Examples for Neural Image Captioning. - Hongge Chen; Huan Zhang 001; Pin-Yu Chen; Jinfeng Yi; Cho-Jui Hsieh (CoRR, 2017)

EAD: Elastic-Net Attacks to Deep Neural Networks via Adversarial Examples. - Pin-Yu Chen; Yash Sharma 001; Huan Zhang 001; Jinfeng Yi; Cho-Jui Hsieh (AAAI, 2018)

Attacking Visual Language Grounding with Adversarial Examples: A Case Study on Neural Image Captioning. - Hongge Chen; Huan Zhang 001; Pin-Yu Chen; Jinfeng Yi; Cho-Jui Hsieh (ACL (1), 2018)

Random Warping Series: A Random Features Method for Time-Series Embedding. - Lingfei Wu 001; Ian En-Hsu Yen; Jinfeng Yi; Fangli Xu; Qi Lei; Michael Witbrock (AISTATS, 2018)

Session Expert: a Lightweight Conference Session Recommender System. - Jinfeng Yi; Qi Lei; Junchi Yan; Wei Sun (IEEE BigData, 2018)

Towards Query Efficient Black-box Attacks: An Input-free Perspective. - Yali Du 001; Meng Fang; Jinfeng Yi; Jun Cheng 002; Dacheng Tao (AISec@CCS, 2018)

Is Robustness the Cost of Accuracy? - A Comprehensive Study on the Robustness of 18 Deep Image Classification Models. - Dong Su; Huan Zhang 001; Hongge Chen; Jinfeng Yi; Pin-Yu Chen; Yupeng Gao (ECCV (12), 2018)

Query-Efficient Black-Box Attack by Active Learning. - Pengcheng Li; Jinfeng Yi; Lijun Zhang 005 (ICDM, 2018)

Evaluating the Robustness of Neural Networks: An Extreme Value Theory Approach. - Tsui-Wei Weng; Huan Zhang 001; Pin-Yu Chen; Jinfeng Yi; Dong Su; Yupeng Gao; Cho-Jui Hsieh; Luca Daniel (ICLR (Poster), 2018)

Self-weighted Multiple Kernel Learning for Graph-based Clustering and Semi-supervised Classification. - Zhao Kang 001; Xiao Lu 004; Jinfeng Yi; Zenglin Xu (IJCAI, 2018)

Identify Susceptible Locations in Medical Records via Adversarial Attacks on Deep Predictive Models. - Mengying Sun; Fengyi Tang; Jinfeng Yi; Fei Wang 001; Jiayu Zhou (KDD, 2018)

Diverse Few-Shot Text Classification with Multiple Metrics. - Mo Yu; Xiaoxiao Guo; Jinfeng Yi; Shiyu Chang; Saloni Potdar; Yu Cheng 001; Gerald Tesauro; Haoyu Wang 002; Bowen Zhou (NAACL-HLT, 2018)

Adaptive Negative Curvature Descent with Applications in Non-convex Optimization. - Mingrui Liu; Zhe Li 008; Xiaoyu Wang 002; Jinfeng Yi; Tianbao Yang (NeurIPS, 2018)

Matrix Completion from Non-Uniformly Sampled Entries. - Yuanyu Wan; Jinfeng Yi; Lijun Zhang 005 (CoRR, 2018)

Defend Deep Neural Networks Against Adversarial Examples via Fixed andDynamic Quantized Activation Functions. - Adnan Siraj Rakin; Jinfeng Yi; Boqing Gong; Deliang Fan (CoRR, 2018)

A Frank-Wolfe Framework for Efficient and Effective Adversarial Attacks. - Jinghui Chen; Jinfeng Yi; Quanquan Gu (CoRR, 2018)

AutoZOOM: Autoencoder-Based Zeroth Order Optimization Method for Attacking Black-Box Neural Networks. - Chun-Chen Tu; Pai-Shun Ting; Pin-Yu Chen; Sijia Liu 001; Huan Zhang 001; Jinfeng Yi; Cho-Jui Hsieh; Shin-Ming Cheng (AAAI, 2019)

How You Act Tells a Lot: Privacy-Leaking Attack on Deep Reinforcement Learning. - Xinlei Pan; Weiyao Wang 001; Xiaoshuai Zhang; Bo Li 026; Jinfeng Yi; Dawn Song (AAMAS, 2019)

Adversarial Structured Neural Network Pruning. - Xingyu Cai; Jinfeng Yi; Fan Zhang 010; Sanguthevar Rajasekaran (CIKM, 2019)

Defending Against Adversarial Attacks Using Random Forest. - Yifan Ding; Liqiang Wang 001; Huan Zhang 001; Jinfeng Yi; Deliang Fan; Boqing Gong (CVPR Workshops, 2019)

Symmetric Cross Entropy for Robust Learning With Noisy Labels. - Yisen Wang 001; Xingjun Ma; Zaiyi Chen; Yuan Luo 003; Jinfeng Yi; James Bailey 001 (ICCV, 2019)

AdvIT: Adversarial Frames Identifier Based on Temporal Consistency in Videos. - Chaowei Xiao; Ruizhi Deng; Bo Li 026; Taesung Lee; Benjamin Edwards; Jinfeng Yi; Dawn Song; Mingyan Liu; Ian M. Molloy (ICCV, 2019)

Universal Stagewise Learning for Non-Convex Problems with Convergence on Averaged Solutions. - Zaiyi Chen; Zhuoning Yuan; Jinfeng Yi; Bowen Zhou 001; Enhong Chen; Tianbao Yang (ICLR (Poster), 2019)

Query-Efficient Hard-label Black-box Attack: An Optimization-based Approach. - Minhao Cheng; Thong Le; Pin-Yu Chen; Huan Zhang 001; Jinfeng Yi; Cho-Jui Hsieh (ICLR (Poster), 2019)

On the Convergence and Robustness of Adversarial Training. - Yisen Wang 001; Xingjun Ma; James Bailey 001; Jinfeng Yi; Bowen Zhou 001; Quanquan Gu (ICML, 2019)

Similarity Preserving Representation Learning for Time Series Clustering. - Qi Lei; Jinfeng Yi; Roman Vaculín; Lingfei Wu 001; Inderjit S. Dhillon (IJCAI, 2019)

Improving the Robustness of Deep Neural Networks via Adversarial Training with Triplet Loss. - Pengcheng Li; Jinfeng Yi; Bowen Zhou 001; Lijun Zhang 005 (IJCAI, 2019)

Sample Adaptive Multiple Kernel Learning for Failure Prediction of Railway Points. - Zhibin Li 002; Jian Zhang 002; Qiang Wu 001; Yongshun Gong; Jinfeng Yi; Christina Kirsch (KDD, 2019)

DTWNet: a Dynamic Time Warping Network. - Xingyu Cai; Tingyang Xu; Jinfeng Yi; Junzhou Huang; Sanguthevar Rajasekaran (NeurIPS, 2019)

Fast Unsupervised Location Category Inference from Highly Inaccurate Mobility Data. - Jinfeng Yi; Qi Lei; Wesley M. Gifford; Ji Liu; Junchi Yan; Bowen Zhou 001 (SDM, 2019)

Reliable Weakly Supervised Learning: Maximize Gain and Maintain Safeness. - Lan-Zhe Guo; Yufeng Li 008; Ming Li 005; Jinfeng Yi; Bowen Zhou 001; Zhi-Hua Zhou (CoRR, 2019)

How You Act Tells a Lot: Privacy-Leakage Attack on Deep Reinforcement Learning. - Xinlei Pan; Weiyao Wang 001; Xiaoshuai Zhang; Bo Li 026; Jinfeng Yi; Dawn Song (CoRR, 2019)

Evaluating the Robustness of Nearest Neighbor Classifiers: A Primal-Dual Perspective. - Lu Wang 031; Xuanqing Liu; Jinfeng Yi; Zhi-Hua Zhou; Cho-Jui Hsieh (CoRR, 2019)

Joint Semantic Domain Alignment and Target Classifier Learning for Unsupervised Domain Adaptation. - Dongdong Chen; Yisen Wang 001; Jinfeng Yi; Zaiyi Chen; Zhi-Hua Zhou (CoRR, 2019)

Defending Against Adversarial Attacks Using Random Forests. - Yifan Ding; Liqiang Wang 001; Huan Zhang 001; Jinfeng Yi; Deliang Fan; Boqing Gong (CoRR, 2019)

Characterizing Attacks on Deep Reinforcement Learning. - Chaowei Xiao; Xinlei Pan; Warren He; Jian Peng 001; Mingjie Sun; Jinfeng Yi; Mingyan Liu; Bo Li 026; Dawn Song (CoRR, 2019)

Enhancing the Robustness of Neural Collaborative Filtering Systems Under Malicious Attacks. - Yali Du 001; Meng Fang; Jinfeng Yi; Chang Xu 002; Jun Cheng 002; Dacheng Tao (IEEE Trans. Multim., 2019)

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

Seq2Sick: Evaluating the Robustness of Sequence-to-Sequence Models with Adversarial Examples. - Minhao Cheng; Jinfeng Yi; Pin-Yu Chen; Huan Zhang 001; Cho-Jui Hsieh (AAAI, 2020)

Potential Passenger Flow Prediction: A Novel Study for Urban Transportation Development. - Yongshun Gong; Zhibin Li 002; Jian Zhang 002; Wei Liu 007; Jinfeng Yi (AAAI, 2020)

Improving Adversarial Robustness Requires Revisiting Misclassified Examples. - Yisen Wang 001; Difan Zou; Jinfeng Yi; James Bailey 001; Xingjun Ma; Quanquan Gu (ICLR, 2020)

Provably Robust Metric Learning. - Lu Wang 031; Xuanqing Liu; Jinfeng Yi; Yuan Jiang 001; Cho-Jui Hsieh (NeurIPS, 2020)

Model-Agnostic Counterfactual Reasoning for Eliminating Popularity Bias in Recommender System. - Tianxin Wei; Fuli Feng; Jiawei Chen 007; Chufeng Shi; Ziwei Wu; Jinfeng Yi; Xiangnan He 001 (CoRR, 2020)

On the Limitations of Denoising Strategies as Adversarial Defenses. - Zhonghan Niu; Zhaoxi Chen 004; Linyi Li 001; Yubin Yang; Bo Li 026; Jinfeng Yi (CoRR, 2020)

Spanning attack: reinforce black-box attacks with unlabeled data. - Lu Wang 031; Huan Zhang 001; Jinfeng Yi; Cho-Jui Hsieh; Yuan Jiang 001 (Mach. Learn., 2020)

PFedAtt: Attention-based Personalized Federated Learning on Heterogeneous Clients. - Zichen Ma; Yu Lu; Wenye Li 001; Jinfeng Yi; Shuguang Cui (ACML, 2021)

Model-Agnostic Counterfactual Reasoning for Eliminating Popularity Bias in Recommender System. - Tianxin Wei; Fuli Feng; Jiawei Chen 007; Ziwei Wu; Jinfeng Yi; Xiangnan He 001 (KDD, 2021)

Leveraging Tripartite Interaction Information from Live Stream E-Commerce for Improving Product Recommendation. - Sanshi Yu; Zhuoxuan Jiang; Dongdong Chen; Shanshan Feng 001; Dongsheng Li 002; Qi Liu 003; Jinfeng Yi (KDD, 2021)

Inferring the Importance of Product Appearance with Semi-supervised Multi-modal Enhancement: A Step Towards the Screenless Retailing. - Yongshun Gong; Jinfeng Yi; Dongdong Chen; Jian Zhang 002; Jiayu Zhou; Zhihua Zhou (ACM Multimedia, 2021)

Fast Certified Robust Training with Short Warmup. - Zhouxing Shi; Yihan Wang; Huan Zhang 001; Jinfeng Yi; Cho-Jui Hsieh (NeurIPS, 2021)

Better Safe Than Sorry: Preventing Delusive Adversaries with Adversarial Training. - Lue Tao; Lei Feng 006; Jinfeng Yi; Sheng-Jun Huang; Songcan Chen (NeurIPS, 2021)

Hierarchical Personalized Federated Learning for User Modeling. - Jinze Wu; Qi Liu 003; Zhenya Huang; Yuting Ning; Hao Wang 076; Enhong Chen; Jinfeng Yi; Bowen Zhou 001 (WWW, 2021)

Provable Defense Against Delusive Poisoning. - Lue Tao; Lei Feng 006; Jinfeng Yi; Sheng-Jun Huang; Songcan Chen (CoRR, 2021)

On the Adversarial Robustness of Visual Transformers. - Rulin Shao; Zhouxing Shi; Jinfeng Yi; Pin-Yu Chen; Cho-Jui Hsieh (CoRR, 2021)

Fast Certified Robust Training via Better Initialization and Shorter Warmup. - Zhouxing Shi; Yihan Wang; Huan Zhang 001; Jinfeng Yi; Cho-Jui Hsieh (CoRR, 2021)

Towards Heterogeneous Clients with Elastic Federated Learning. - Zichen Ma; Yu Lu; Zihan Lu; Wenye Li 001; Jinfeng Yi; Shuguang Cui (CoRR, 2021)

Adversarial Attack across Datasets. - Yunxiao Qin; Yuanhao Xiong; Jinfeng Yi; Cho-Jui Hsieh (CoRR, 2021)

How and When Adversarial Robustness Transfers in Knowledge Distillation? - Rulin Shao; Jinfeng Yi; Pin-Yu Chen; Cho-Jui Hsieh (CoRR, 2021)

Federated Two-stage Learning with Sign-based Voting. - Zichen Ma; Zihan Lu; Yu Lu; Wenye Li 001; Jinfeng Yi; Shuguang Cui (CoRR, 2021)

With False Friends Like These, Who Can Notice Mistakes? - Lue Tao; Lei Feng 006; Jinfeng Yi; Songcan Chen (AAAI, 2022)

Robust Text CAPTCHAs Using Adversarial Examples. - Rulin Shao; Zhouxing Shi; Jinfeng Yi; Pin-Yu Chen; Cho-Jui Hsieh (IEEE Big Data, 2022)

How to Robustify Black-Box ML Models? A Zeroth-Order Optimization Perspective. - Yimeng Zhang; Yuguang Yao; Jinghan Jia; Jinfeng Yi; Mingyi Hong 001; Shiyu Chang; Sijia Liu 001 (ICLR, 2022)

A Simple yet Universal Strategy for Online Convex Optimization. - Lijun Zhang 005; Guanghui Wang 006; Jinfeng Yi; Tianbao Yang (ICML, 2022)

Understanding Clipping for Federated Learning: Convergence and Client-Level Differential Privacy. - Xinwei Zhang 001; Xiangyi Chen; Mingyi Hong 001; Steven Wu 001; Jinfeng Yi (ICML, 2022)

Can Adversarial Training Be Manipulated By Non-Robust Features? - Lue Tao; Lei Feng 006; Hongxin Wei; Jinfeng Yi; Sheng-Jun Huang; Songcan Chen (NeurIPS, 2022)

Smoothed Online Convex Optimization Based on Discounted-Normal-Predictor. - Lijun Zhang 005; Wei Jiang 029; Jinfeng Yi; Tianbao Yang (NeurIPS, 2022)

Adaptive Feature Generation for Online Continual Learning from Imbalanced Data. - Yingchun Jian; Jinfeng Yi; Lijun Zhang 005 (PAKDD (1), 2022)

On the Adversarial Robustness of Vision Transformers. - Rulin Shao; Zhouxing Shi; Jinfeng Yi; Pin-Yu Chen; Cho-Jui Hsieh (Trans. Mach. Learn. Res., 2022)

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

FedAvg Converges to Zero Training Loss Linearly for Overparameterized Multi-Layer Neural Networks. - Bingqing Song; Prashant Khanduri; Xinwei Zhang 001; Jinfeng Yi; Mingyi Hong 001 (ICML, 2023)

Efficient Algorithms for Generalized Linear Bandits with Heavy-tailed Rewards. - Bo Xue 004; Yimu Wang; Yuanyu Wan; Jinfeng Yi; Lijun Zhang 005 (NeurIPS, 2023)

Stochastic Graphical Bandits with Heavy-Tailed Rewards. - Yutian Gou; Jinfeng Yi; Lijun Zhang 005 (UAI, 2023)

Trustworthy AI: From Principles to Practices. - Bo Li 026; Peng Qi 003; Bo Liu; Shuai Di; Jingen Liu; Jiquan Pei; Jinfeng Yi; Bowen Zhou 001 (ACM Comput. Surv., 2023)

Federated User Modeling from Hierarchical Information. - Qi Liu 003; Jinze Wu; Zhenya Huang; Hao Wang 076; Yuting Ning; Ming Chen; Enhong Chen; Jinfeng Yi; Bowen Zhou 001 (ACM Trans. Inf. Syst., 2023)

Self-supervised Graph Neural Network for Mechanical CAD Retrieval. - Yuhan Quan; Huan Zhao; Jinfeng Yi; Yuqiang Chen (CoRR, 2024)

Continual Learning With Unknown Task Boundary. - Xiaoxie Zhu; Jinfeng Yi; Lijun Zhang 005 (IEEE Trans. Neural Networks Learn. Syst., 2025)