Dou, Dejing

54 publications

ICML 2025 Flexible, Efficient, and Stable Adversarial Attacks on Machine Unlearning Zihan Zhou, Yang Zhou, Zijie Zhang, Lingjuan Lyu, Da Yan, Ruoming Jin, Dejing Dou

CVPR 2025 Reasoning to Attend: Try to Understand How <SEG> Token Works Rui Qian, Xin Yin, Dejing Dou

AAAI 2024 FedASMU: Efficient Asynchronous Federated Learning with Dynamic Staleness-Aware Model Update Ji Liu, Juncheng Jia, Tianshi Che, Chao Huo, Jiaxiang Ren, Yang Zhou, Huaiyu Dai, Dejing Dou

AAAI 2024 G-LIME: Statistical Learning for Local Interpretations of Deep Neural Networks Using Global Priors (Abstract Reprint) Xuhong Li, Haoyi Xiong, Xingjian Li, Xiao Zhang, Ji Liu, Haiyan Jiang, Zeyu Chen, Dejing Dou

MLJ 2024 Towards Accurate Knowledge Transfer via Target-Awareness Representation Disentanglement Xingjian Li, Di Hu, Xuhong Li, Haoyi Xiong, Cheng-Zhong Xu, Dejing Dou

TMLR 2023 Beyond Intuition: Rethinking Token Attributions Inside Transformers Jiamin Chen, Xuhong Li, Lei Yu, Dejing Dou, Haoyi Xiong

MLJ 2023 Cross-Model Consensus of Explanations and Beyond for Image Classification Models: An Empirical Study Xuhong Li, Haoyi Xiong, Siyu Huang, Shilei Ji, Dejing Dou

MLJ 2023 Distilling Ensemble of Explanations for Weakly-Supervised Pre-Training of Image Segmentation Models Xuhong Li, Haoyi Xiong, Yi Liu, Dingfu Zhou, Zeyu Chen, Yaqing Wang, Dejing Dou

ICML 2023 Fast Federated Machine Unlearning with Nonlinear Functional Theory Tianshi Che, Yang Zhou, Zijie Zhang, Lingjuan Lyu, Ji Liu, Da Yan, Dejing Dou, Jun Huan

AAAI 2023 Learning from Training Dynamics: Identifying Mislabeled Data Beyond Manually Designed Features Qingrui Jia, Xuhong Li, Lei Yu, Jiang Bian, Penghao Zhao, Shupeng Li, Haoyi Xiong, Dejing Dou

TMLR 2023 Pareto Optimization for Active Learning Under Out-of-Distribution Data Scenarios Xueying Zhan, Zeyu Dai, Qingzhong Wang, Qing Li, Haoyi Xiong, Dejing Dou, Antoni B. Chan

TMLR 2023 SMILE: Sample-to-Feature Mixup for Efficient Transfer Learning Xingjian Li, Haoyi Xiong, Cheng-zhong Xu, Dejing Dou

CVPR 2023 Spectral Enhanced Rectangle Transformer for Hyperspectral Image Denoising Miaoyu Li, Ji Liu, Ying Fu, Yulun Zhang, Dejing Dou

ICML 2022 Accelerated Federated Learning with Decoupled Adaptive Optimization Jiayin Jin, Jiaxiang Ren, Yang Zhou, Lingjuan Lyu, Ji Liu, Dejing Dou

NeurIPS 2022 AutoMS: Automatic Model Selection for Novelty Detection with Error Rate Control Yifan Zhang, Haiyan Jiang, Haojie Ren, Changliang Zou, Dejing Dou

AAAI 2022 Efficient Device Scheduling with Multi-Job Federated Learning Chendi Zhou, Ji Liu, Juncheng Jia, Jingbo Zhou, Yang Zhou, Huaiyu Dai, Dejing Dou

MLJ 2022 Exploring the Common Principal Subspace of Deep Features in Neural Networks Haoran Liu, Haoyi Xiong, Yaqing Wang, Haozhe An, Dejing Dou, Dongrui Wu

IJCAI 2022 FedDUAP: Federated Learning with Dynamic Update and Adaptive Pruning Using Shared Data on the Server Hong Zhang, Ji Liu, Juncheng Jia, Yang Zhou, Huaiyu Dai, Dejing Dou

NeurIPS 2022 Generative Time Series Forecasting with Diffusion, Denoise, and Disentanglement Yan Li, Xinjiang Lu, Yaqing Wang, Dejing Dou

AAAI 2022 GeomGCL: Geometric Graph Contrastive Learning for Molecular Property Prediction Shuangli Li, Jingbo Zhou, Tong Xu, Dejing Dou, Hui Xiong

MLOSS 2022 InterpretDL: Explaining Deep Models in PaddlePaddle Xuhong Li, Haoyi Xiong, Xingjian Li, Xuanyu Wu, Zeyu Chen, Dejing Dou

ECML-PKDD 2022 Meta Hierarchical Reinforced Learning to Rank for Recommendation: A Comprehensive Study in MOOCs Yuchen Li, Haoyi Xiong, Linghe Kong, Rui Zhang, Dejing Dou, Guihai Chen

NeurIPSW 2022 SMILE: Sample-to-Feature MIxup for Efficient Transfer LEarning Xingjian Li, Haoyi Xiong, Cheng-zhong Xu, Dejing Dou

CVPR 2021 Adaptive Consistency Regularization for Semi-Supervised Transfer Learning Abulikemu Abuduweili, Xingjian Li, Humphrey Shi, Cheng-Zhong Xu, Dejing Dou

MLJ 2021 AgFlow: Fast Model Selection of Penalized PCA via Implicit Regularization Effects of Gradient Flow Haiyan Jiang, Haoyi Xiong, Dongrui Wu, Ji Liu, Dejing Dou

CVPR 2021 ArtFlow: Unbiased Image Style Transfer via Reversible Neural Flows Jie An, Siyu Huang, Yibing Song, Dejing Dou, Wei Liu, Jiebo Luo

AAAI 2021 C-Watcher: A Framework for Early Detection of High-Risk Neighborhoods Ahead of COVID-19 Outbreak Congxi Xiao, Jingbo Zhou, Jizhou Huang, An Zhuo, Ji Liu, Haoyi Xiong, Dejing Dou

AAAI 2021 Community-Aware Multi-Task Transportation Demand Prediction Hao Liu, Qiyu Wu, Fuzhen Zhuang, Xinjiang Lu, Dejing Dou, Hui Xiong

NeurIPSW 2021 Explaining Information Flow Inside Vision Transformers Using Markov Chain Tingyi Yuan, Xuhong Li, Haoyi Xiong, Hui Cao, Dejing Dou

ICML 2021 Expressive 1-Lipschitz Neural Networks for Robust Multiple Graph Learning Against Adversarial Attacks Xin Zhao, Zeru Zhang, Zijie Zhang, Lingfei Wu, Jiayin Jin, Yang Zhou, Ruoming Jin, Dejing Dou, Da Yan

NeurIPS 2021 Generalized DataWeighting via Class-Level Gradient Manipulation Can Chen, Shuhao Zheng, Xi Chen, Erqun Dong, Xue Liu, Hao Liu, Dejing Dou

ICML 2021 Integrated Defense for Resilient Graph Matching Jiaxiang Ren, Zijie Zhang, Jiayin Jin, Xin Zhao, Sixing Wu, Yang Zhou, Yelong Shen, Tianshi Che, Ruoming Jin, Dejing Dou

AAAI 2021 Joint Air Quality and Weather Prediction Based on Multi-Adversarial Spatiotemporal Networks Jindong Han, Hao Liu, Hengshu Zhu, Hui Xiong, Dejing Dou

AAAI 2021 Out-of-Town Recommendation with Travel Intention Modeling Haoran Xin, Xinjiang Lu, Tong Xu, Hao Liu, Jingjing Gu, Dejing Dou, Hui Xiong

NeurIPS 2021 Property-Aware Relation Networks for Few-Shot Molecular Property Prediction Yaqing Wang, Abulikemu Abuduweili, Quanming Yao, Dejing Dou

ICCV 2021 Semi-Supervised Active Learning with Temporal Output Discrepancy Siyu Huang, Tianyang Wang, Haoyi Xiong, Jun Huan, Dejing Dou

AAAI 2021 Temporal Relational Modeling with Self-Supervision for Action Segmentation Dong Wang, Di Hu, Xingjian Li, Dejing Dou

NeurIPS 2021 Validating the Lottery Ticket Hypothesis with Inertial Manifold Theory Zeru Zhang, Jiayin Jin, Zijie Zhang, Yang Zhou, Xin Zhao, Jiaxiang Ren, Ji Liu, Lingfei Wu, Ruoming Jin, Dejing Dou

AAAI 2020 A Joint Model for Definition Extraction with Syntactic Connection and Semantic Consistency Amir Pouran Ben Veyseh, Franck Dernoncourt, Dejing Dou, Thien Huu Nguyen

NeurIPS 2020 Adversarial Attacks on Deep Graph Matching Zijie Zhang, Zeru Zhang, Yang Zhou, Yelong Shen, Ruoming Jin, Dejing Dou

ECCV 2020 Cross-Task Transfer for Geotagged Audiovisual Aerial Scene Recognition Di Hu, Xuhong Li, Lichao Mou, Pu Jin, Dong Chen, Liping Jing, Xiaoxiang Zhu, Dejing Dou

NeurIPS 2020 Discriminative Sounding Objects Localization via Self-Supervised Audiovisual Matching Di Hu, Rui Qian, Minyue Jiang, Xiao Tan, Shilei Wen, Errui Ding, Weiyao Lin, Dejing Dou

IJCAI 2020 Generating Person Images with Appearance-Aware Pose Stylizer Siyu Huang, Haoyi Xiong, Zhi-Qi Cheng, Qingzhong Wang, Xingran Zhou, Bihan Wen, Jun Huan, Dejing Dou

AAAI 2020 Learning Conceptual-Contextual Embeddings for Medical Text Xiao Zhang, Dejing Dou, Ji Wu

AAAI 2020 Multi-View Consistency for Relation Extraction via Mutual Information and Structure Prediction Amir Pouran Ben Veyseh, Franck Dernoncourt, My Tra Thai, Dejing Dou, Thien Huu Nguyen

ICLR 2020 NormLime: A New Feature Importance Metric for Explaining Deep Neural Networks Isaac Ahern, Adam Noack, Luis Guzman-Nateras, Dejing Dou, Boyang Li, Jun Huan

ICLR 2020 Pay Attention to Features, Transfer Learn Faster CNNs Kafeng Wang, Xitong Gao, Yiren Zhao, Xingjian Li, Dejing Dou, Cheng-Zhong Xu

ICML 2020 RIFLE: Backpropagation in Depth for Deep Transfer Learning Through Re-Initializing the Fully-Connected LayEr Xingjian Li, Haoyi Xiong, Haozhe An, Cheng-Zhong Xu, Dejing Dou

ICML 2020 Scalable Differential Privacy with Certified Robustness in Adversarial Learning Hai Phan, My T. Thai, Han Hu, Ruoming Jin, Tong Sun, Dejing Dou

IJCAI 2019 Heterogeneous Gaussian Mechanism: Preserving Differential Privacy in Deep Learning with Provable Robustness NhatHai Phan, Minh N. Vu, Yang Liu, Ruoming Jin, Dejing Dou, Xintao Wu, My T. Thai

IJCAI 2019 Improving Cross-Domain Performance for Relation Extraction via Dependency Prediction and Information Flow Control Amir Pouran Ben Veyseh, Thien Huu Nguyen, Dejing Dou

MLJ 2017 Preserving Differential Privacy in Convolutional Deep Belief Networks NhatHai Phan, Xintao Wu, Dejing Dou

AAAI 2016 A Probabilistic Approach to Knowledge Translation Shangpu Jiang, Daniel Lowd, Dejing Dou

AAAI 2016 Differential Privacy Preservation for Deep Auto-Encoders: An Application of Human Behavior Prediction NhatHai Phan, Yue Wang, Xintao Wu, Dejing Dou