Publication List

2024

1. [NMI] Ning Wang*, Jiang Bian*, Xuhong Li, Yuchen Li, Shahid Mumtaz, Linge Kong^, Haoyi Xiong*^. Multi-purpose RNA Language Modeling with Motif-aware Pre-training and Type-guided Fine-tuning. Nature Machine Intelligence, 2024

2. [TKDE] Shuangli Li, Jingbo Zhou^, Tong Xu, Liang Huang, Fan Wang, Haoyi Xiong, Weili Huang, Dejing Dou, Hui Xiong^. GIANT: Protein-Ligand Binding Affinity Prediction via Geometry-aware Interactive Graph Neural Network. IEEE Transactions on Knowledge and Data Engineering, IEEE. 

3. [TMLR] Xueying Zhan, Zeyu Dai, Qingzhong Wang, Qing Li, Haoyi Xiong, Dejing Dou, and Antoni B. Chan. Pareto Optimization for Active Learning under Out-of-Distribution Data Scenarios. Transactions on Machine Learning Research. [PDF] [OpenReview]

4. [IJCAI'24] Jingyang Deng, Xingjian Li, Haoyi Xiong, Xiaoguang Hu, Jinwen Ma^. Geometry-Guided Conditional Adaption for Surrogate Models of Large-Scale 3D PDEs on Arbitrary Geometries. 2024 International Joint Conference on Artificial Intelligence. 

5. [IJCAI'24] Yuchen Li, Haoyi Xiong^, Linghe Kong^, Jiang Bian, Shuaiqiang Wang, Guihai Chen, and Dawei Yin. GS2P: A Generative Pre-trained Learning to Rank Model with Over-parameterization for Web-Scale Search (Extended Abstract). 2024 International Joint Conference on Artificial Intelligence.  (Sister Conference Best Paper Track - DSAA'23 Best Paper Award).

6. [IJCAI'24] Yuchen Li, Haoyi Xiong^, Linghe Kong^, Zeyi Sun, Hongyang Chen, Shuaiqiang Wang, and Dawei Yin. MPGraf: a Modular and Pre-trained Graphformer for Learning to Rank at Web-scale (Extended Abstract). 2024 International Joint Conference on Artificial Intelligence.  (Sister Conference Best Paper Track - ICDM'23 Best Student Paper Award).

7. [AAAI'24] Xuhong Li, Haoyi Xiong^, Xingjian Li, Xiao Zhang, Ji Liu, Haiyan Jiang, Zeyu Chen, Dejing Dou. G–LIME: Statistical Learning for Local Interpretations of Deep Neural Networks Using Global Priors (Abstract Reprint). In Proceedings of the Thirty-Eight AAAI Conference on Artificial Intelligence, 2024.  (an earlier version has been published by AIJ)

8. [MLST] Haoyi Xiong^, Xuhong Li, Dongrui Wu, Zhanxing Zhu, and Dejing Dou. Stochastic Gradient Descent with Random Label Noises: Doubly Stochastic Models and Inference Stabilizer. Machine Learning Science and Technology, IOP. [PDF]

9. [MLJ] Xingjian Li^, Di Hu, Xuhong Li, Haoyi Xiong, Chengzhong Xu, and Dejing Dou. Towards accurate knowledge transfer via target-awareness representation disentanglement. Machine Learning, Springer.

10. [MLJ] Yuchen Li, Haoyi Xiong^, Linghe Kong^, Jiang Bian, Shuaiqiang Wang, Guihai Chen, and Dawei Yin. GS2P: A Generative Pre-trained Learning to Rank Model with Over-parameterization for Web-Scale Search. Machine Learning (DSAA 2023 Best Paper Awards - Journal Track), Springer. 

11. [TOMM] Jiang Bian, Xuhong Li, Tao Wang, Qingzhong Wang, Jun Huang, Chen Liu, Jun Zhao, Feixiang Lu, Dejing Dou, and Haoyi Xiong^. P2ANet: Large-Scale Benchmark for Dense Action Detection from Table Tennis Match Broadcasting Videos. ACM Transactions on Multimedia Computing Communications and Applications (TOMM).  [PDF]

12. [TNNLS] Siyu Huang, Tianyang Wang, Haoyi Xiong, Bihan Wen^, Jun Huan, and Dejing Dou. Temporal Output Discrepancy for Loss Estimation-based Active Learning. IEEE Transactions on Neural Networks and Learning Systems, IEEE. [PDF]

2023

13. [TSC] Yuchen Li, Haoyi Xiong^, Linghe Kong^, Rui Zhang, Fangqin Xu, Guihai Chen, Minglu Li. MHRR: MOOCs Recommender Service with Meta Hierarchical Reinforced Ranking. IEEE Transactions on Services Computing, 2023, IEEE. 

14. [AIJ] Xuhong Li, Haoyi Xiong^, Xingjian Li, Xiao Zhang, Ji Liu, Haiyan Jiang, Zeyu Chen, Dejing Dou. G-LIME: Statistical Learning for Local Interpretations of Deep Neural Networks using Global Priors. Artificial Intelligence, 2023. [PDF]

15. [TMLR] Jiamin Chen*, Xuhong Li*, Lei Yu, Dejing Dou, Haoyi Xiong. Beyond Intuition: Rethinking Token Attributions inside Transformers. Transactions on Machine Learning Research, 2023. [PDF] [OpenReview] [Codes]

16. [TMLR] Xingjian Li*, Haoyi Xiong*^, Dejing Dou, and Cheng-zhong Xu. SMILE: Sample-to-feature Mixup for Efficient Transfer Learning.  Transactions on Machine Learning Research, 2023, [PDF] [OpenReview][Codes].

17. [TMC] Jiang Bian*, Haoyi Xiong*^, Zhiyuan Wang, Jingbo Zhou, Shilei Ji, Hongyang Chen, Daqing Zhang, and Dejing Dou. AFCS: Aggregation-Free Spatial-Temporal Mobile Community Sensing. IEEE Transactions on Mobile Computing, 2023, IEEE. [PDF] 

18. [TSC] Jiang Bian, Jizhou Huang, Shilei Ji, Yuan Liao, Xuhong Li, Qingzhong Wang, Jingbo Zhou, Yaqing Wang, Dejing Dou, and Haoyi Xiong^. Feynman: Federated Learning-based Advertising for Ecosystems-Oriented Mobile Apps Recommendation. IEEE Transactions on Services Computing, 2023, IEEE. [PDF]

19. [TKDE] Yuchen Li, Haoyi Xiong^, Qingzhong Wang, Linghe Kong^, Hao Liu, Haifang Li, Jiang Bian, Shuaiqiang Wang, Guihai Chen, Dejing Dou, Dawei Yin. COLTR: Semi-supervised Learning to Rank with Co-training and Over-parameterization for Web Search. IEEE Transactions on Knowledge and Data Engineering, 2023, IEEE. [PDF]

20. [TKDE] Jindong Han*, Hao Liu*^, Haoyi Xiong, and Jing Yang. Semi-Supervised Air Quality Forecasting via Self-Supervised Hierarchical Graph Neural Network. IEEE Transactions on Knowledge and Data Engineering, 2023, IEEE. [PDF]

21. [TON] En Wang, Mijia Zhang, Wenbin Liu^, Haoyi Xiong, Bo Yang, Yongjian Yang, Jie Wu. Outlier-Concerned Data Completion Exploiting Intra- and Inter-data Correlations in Sparse CrowdSensing. IEEE/ACM Transactions on Networking, 2022, IEEE.

22. [NeurIPS'23] Xuhong Li, Mengnan Du, Jiamin Chen, Yekun Chai, Himabindu Lakkaraju, Haoyi Xiong^. M4: A Unified XAI Benchmark for Faithfulness Evaluation of Feature Attribution Methods across Metrics, Modalities and Models. NeurIPS 2023 Track Datasets and Benchmarks, 2023. [PDF]

23. [KDD'23] Yuchen Li, Haoyi Xiong^, Linghe Kong^, Qingzhong Wang, Shuaiqiang Wang, Guihai Chen, and Dawei Yin. S2phere: Semi-Supervised Pre-training for Web Search over Heterogeneous Learning to Rank Data. The 29th SIGKDD Conference on Knowledge Discovery and Data Mining, 2023. [PDF]

24. [KDD'23] Xuewu Jiao, Weibin Li, Xinxuan wu, Wei Hu, Miao Li, Jiang Bian, Siming Dai, Xinsheng Luo, Mingqing Hu, Zhengjie Huang, Danlei Feng, Junchao Yang, Shikun Feng, Haoyi Xiong, Dianhai Yu, Shuanglong Li, Jingzhou He, Yanjun Ma, Lin Liu. PGLBox: Multi-GPU Graph Learning Framework for Web-Scale Recommendation.  The 29th SIGKDD Conference on Knowledge Discovery and Data Mining, 2023. [PDF]

25. [AAAI'23] Qingrui Jia*, Xuhong Li*, Lei Yu, Jiang Bian, Penghao Zhao, Shupeng Li, Haoyi Xiong^ and Dejing Dou. Learning from Training Dynamics: Identifying Mislabeled Data Beyond Manually Designed Features. In Proceedings of the Thirty-Seven AAAI Conference on Artificial Intelligence, 2023. [PDF]

26. [ICCV'23] Andong Deng*, Xingjian Li*, Di Hu^, Tianyang Wang, Haoyi Xiong and Chengzhong Xu. Towards Inadequately Pre-trained Models in Transfer Learning. International Conference on Computer Vision, 2023. [PDF]

27. [ICDE'23] Yan Li, Xinjiang Lu^, Haoyi Xiong, Jian Tang, Jiantao Su, Bo Jin, Dejing Dou. Towards Long-Term Time-Series Forecasting: Feature, Pattern and Distribution. IEEE International Conference on Data Engineering, 2023. [PDF]

28. [MIDL'23] Junde Wu, Rao Fu, Huihui Fang, Yu Zhang, Yehui Yang, Haoyi Xiong, Huiying Liu, Yanwu Xu^. MedSegDiff: Medical Image Segmentation with Diffusion Probabilistic Model. In Proceedings of Medical Imaging with Deep Learning Conference, 2023, PMLR. [PDF]

29. [TMM] Fei Wu*, Qingzhong Wang*^, Jiang Bian*, Ning Ding, Feixiang Lu, Jun Cheng, Dejing Dou, and Haoyi Xiong^. A Survey on Video Action Recognition in Sports: Datasets, Methods and Applications. IEEE Transactions on Multimedia (TMM). [PDF]

30. [MLJ] Xuhong Li, Haoyi Xiong^, Yi Liu, Dingfu Zhou, Zeyu Chen，Yaqing Wang, and Dejing Dou. Distilling Ensemble of Explanations for Weakly-Supervised Pre-Training of Image Segmentation Models. Machine Learning, 2022, Springer. [PDF]

31. [DAMI] Ashkan Farhangi*, Jiang Bian*, Arthur Huang, Haoyi Xiong, Jun Wang, and Zhishan Guo^. AA-Forecast: Anomaly-Aware Forecast for Extreme Events. Data Mining and Knowledge Discovery, 2022, Springer. [PDF]

32. [TITS] Nicholas Gray, Megan Moraes, Jiang Bian, Allen Tian, Alex Wang, Haoyi Xiong, and Zhishan Guo^. GLARE: A Dataset for Traffic Sign Detection in Sun Glare. IEEE Transactions on Intelligent Transportation Systems (TITS), IEEE. [PDF]

33. [PR] Xingjian Li, Abulikemu Abuduweili, Humphrey Shi*, Pengkun Yang, Dejing Dou, Haoyi Xiong, Chengzhong Xu. Semi-supervised transfer learning with hierarchical self-regularization. Pattern Recognition, Elsevier. [PDF]

34. [ICDM'23] Yuchen Li, Haoyi Xiong^, Linghe Kong^, Zeyi Sun, Hongyang Chen, Shuaiqiang Wang, and Dawei Yin. MPGraf: a Modular and Pre-trained Graphformer for Learning to Rank at Web-scale. The 23rd IEEE International Conference on Data Mining, 2023. (ICDM'23 Best Student Paper Award)

35. [ICDM'23] Xuhong Li, Xuanyu Wu, Linghe Kong, Xiao Zhang, Siyu Huang, Dejing Dou, and Haoyi Xiong^. ContRE: A Complementary Measure for Robustness Evaluation of Deep Networks via Contrastive Examples. The 23rd IEEE International Conference on Data Mining, 2023.

36. [ECML/PKDD'23] Yuchen Li , Haoyi Xiong^, Linghe Kong^, Shuaiqiang Wang, Zeyi Sun, Hongyang Chen, Guihai Chen, and Dawei Yin. LtrGCN: Large-Scale Graph Convolutional Networks-based Learning to Rank for Web Search. The 2023 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2023. 

37. [ECML/PKDD'23] Zeren Zhang, Xingjian Li, Tianyang Wang, Tao Hong, Jinwen Ma, Haoyi Xiong, Cheng-Zhong Xu. Overcoming Catastrophic Forgetting for Fine-tuning Pre-trained GANs. The 2023 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2023. 

38. [TCC] Ji Liu^, Lei Mo, Sijia Yang, Jingbo Zhou, Shilei Ji, Haoyi Xiong, and Dejing Dou. Data Placement for Multi-Tenant Data Federation on the Cloud. IEEE Transactions on Cloud Computing, 2022, IEEE. [PDF]

39. [BMC BIOINFO] Jianqiu Wu, Hongyang Chen^, Minhao Cheng and Haoyi Xiong. CurvAGN: Curvature-based Adaptive Graph Neural Networks for Predicting Protein-Ligand Binding Affinity. BMC Bioinformatics, 2023, BMC [PDF]

40. [ISBI'23] Yuxuan Zhang, Qingzhong Wang, Jiang Bian, Yi Liu, Yanwu Xu, Dejing Dou, and Haoyi Xiong^. Video4MRI: An Empirical Study on Brain Magnetic Resonance Image Analytics with CNN-based Video Classification Frameworks. IEEE International Symposium on Biomedical Imaging, 2023. 

41. [MIUA'23] Ziqi Wen*, Qingzhong Wang*, Jiang Bian, Xuhong Li, Yi Liu, and Haoyi Xiong^. Context Matters: Cross-domain Cell Detection in Histopathology Images via Contextual Regularization. 27th Conference on Medical Image Understanding and Analysis, 2023. Springer.

42. [ClinicalNLP@ACL’23] Jiamin Chen, Xuhong Li, Junting Xi, Lei Yu, and Haoyi Xiong. Rare Codes Count: Mining Inter-code Relations for Long-tail Clinical Text Classification. The 5th Clinical Natural Language Processing Workshop, 2023, ACL. 

2022

43. [HDS] Zhiyuan Wang*^, Haoyi Xiong*, Mingyue Tang, Tabor E. Flickinger, Mehdi Boukhechba, Laura E. Barnes . Mobile Sensing in the COVID-19 Era: A Review . Health Data Science  (Science Partner Journal ), 2022, AAAS. [PDF]

44. [JMLR] Xuhong Li, Haoyi Xiong^, Xingjian Li, Xuanyu Wu, Zeyu Chen, and Dejing Dou. InterpretDL: Explaining Deep Models in PaddlePaddle. Journal of Machine Learning Research, 2022. [PDF] (source repo https://github.com/PaddlePaddle/InterpretDL)

45. [TMLR] Fan Wang, Hao Tian, Haoyi Xiong, Hua Wu, Jie Fu, Yang Cao, Kang Yu, Haifeng Wang. Evolving Decomposed Plasticity Rules for Information-Bottlenecked Meta-Learning. Transactions on Machine Learning Research, 2022. [OpenReview] [Codes][Video]

46. [INFOCOM'22] En Wang, Mijia Zhang, Yuanbo Xu, Haoyi Xiong, and Yongjian Yang. Spatiotemporal Fracture Data Inference in Sparse Urban CrowdSensing. the 2022 IEEE International Conference on Computer Communications, 2022.

47. [AAAI'22] Yihang Yin, Qingzhong Wang, Siyu Huang, Haoyi Xiong, and Xiang Zhang. AutoGCL: Automated Graph Contrastive Learning via Learnable View Generators. In Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022.

48. [MICCAI'22] Weibin Liao, Haoyi Xiong^, Qingzhong Wang, Yan Mo, Xuhong Li, Yi Liu, Zeyu Chen, Siyu Huang, and Dejing Dou. MUSCLE: Multi-task Self-supervised Continual Learning to Pre-train Deep Models for X-ray Images of Multiple Body Parts. Medical Image Computing and Computer Assisted Interventions, 2022.

49.  [TKDD] Haoyi Xiong, Ruosi Wan, Jian Zhao^, Zeyu Chen, Xingjian Li, Zhanxing Zhu, and Jun Huan. GroD: Deep Learning with Gradients Orthogonal Decomposition for Knowledge Transfer, Distillation, and Adversarial Training. ACM Transactions on Knowledge Discovery from Data (TKDD-22), 2022, ACM. [PDF]

50. [TKDD] Xingjian Li*, Haoyi Xiong*^, Zeyu Chen, Ji Liu, Jun Huan, Dejing Dou, and Cheng-Zhong Xu. Knowledge Distillation with Attention for Deep Transfer Learning of Convolutional Networks. ACM Transactions on Knowledge Discovery from Data, 2022, ACM. [PDF]

51. [KAIS] Xuhong Li, Haoyi Xiong^, Xingjian Li, Xuanyu Wu, Xiao Zhang, Jiang Bian, and Dejing Dou. Interpretable Deep Learning: Interpretations, Interpretability, Trustworthiness, and Beyond. Knowledge and Information Systems (KAIS-22), 2022, Springer. [PDF]

52. [KAIS] Ji Liu^, Jizhou Huang, Yang Zhou, Xuhong Li, Shilei Ji, Haoyi Xiong, Dejing Dou. From Distributed Machine Learning to Federated Learning: A Survey.  Knowledge and Information Systems, 2022, Springer. [PDF]

53. [MLJ] Haoran Liu, Haoyi  Xiong^,  Yaqing  Wang,  Haozhe An,  Xuhong Li,  Dongrui Wu, and Dejing Dou.  Exploring the Common Principal Subspace of Deep Features in Neural Networks. Machine Learning, 2022, Springer. [PDF]

54. [ECML/PKDD'22] Yuchen Li, Haoyi Xiong, Linghe Kong^, Rui Zhang, Dejing Dou, and Guihai Chen. Meta Hierarchical Reinforced Learning to Rank for Recommendation: A Comprehensive Study in MOOCs, European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2022.

55. [NAACL'22 Findings] Yaqing Wang*, Tian Xin*, Haoyi Xiong^, Yueyang Li, Zeyu Chen^, Sheng Guo, and Dejing Dou. RGL: A Simple yet Effective Relation Graph Augmented Prompt-based Tuning Approach for Few-Shot Learning. Findings of Annual Conference of the North American Chapter of the ACL, 2022.

56. [IOTJ] Zhiyuan Wang*, Haoyi Xiong*^, Jie Zhang, Sijia Yang, Mehdi Boukhechba, Daqing Zhang, Laura E. Barnes, and Dejing Dou. From Personalized Medicine to Population Health: A Survey of mHealth Sensing Techniques. IEEE Internet of Things Journal, 2022, IEEE. [PDF]

57.  [IOTJ] Jiang Bian*, Abdullah Al Arafat*, Haoyi Xiong^, Jing Li, Li Li, Hongyang Chen, Dejing Dou, Jun Wang, and Zhishan Guo^. Machine Learning in Real-Time Internet of Things (IoT) Systems: A Survey. IEEE Internet of Things Journal, 2022, IEEE.

58. .[IOTJ] Jie Zhang, Yang Li, Haoyi Xiong, Dejing Dou, Chunyan Miao, Daqing Zhang^. HandGest: Hierarchical Sensing for Robust in-the-air Handwriting Recognition with Commodity WiFi Devices. IEEE Internet of Things Journal, 2022, IEEE.

59. [ICASSP'22] Siyu Huang, Haoyi Xiong, Tianyang Wang, Bihan Wen, Qingzhong Wang, Zeyu Chen, Jun Huan, and Dejing Dou. Parameter-Free Style Projection for Arbitrary Style Transfer. The 2022 International Conference on Acoustics, Speech, & Signal Processing, 2022.

60. Xueying Zhan, Qingzhong Wang, Kuan-hao Huang, Haoyi Xiong, Dejing Dou, and Antoni B. Chan. A Comparative Survey of Deep Active Learning. NeurIPS Human in the Loop Learning Workshop (HILL@NeurIPS’22), 2022. (source repo https: //github.com/SineZHAN/deepALplus) 

61. Qingrui Jia, Xuhong Li∗, Lei Yu, Jiang Bian, Penghao Zhao, Shupeng Li, Haoyi Xiong and Dejing Dou. Learning from Training Dynamics: Identifying Mislabeled Data Beyond Manually Designed Features. ICML Workshop on Benchmarking Data for Data-Centric AI (DataPerf@ICML’22), 2022. (source repo https:// github.com/PaddlePaddle/InterpretDL/)

62. Lutao Chu, Yi Liu, Zewu Wu, Shiyu Tang, Guowei Chen, Yuying Hao, Juncai Peng, Zhiliang Yu, Zeyu Chen, Baohua Lai and Haoyi Xiong. PP-HumanSeg: Connectivity-Aware Portrait Segmentation with a Large-Scale Teleconferencing Video Dataset. 4th International Workshop on Human Activity Detection in multi-camera, Continuous, long-duration Video, at the IEEE Winter Conference on Applications of Computer Vision (HADCV@WACV’22), 2022, IEEE/CVF. (source repo https://github.com/PaddlePaddle/PaddleSeg/blob/release/2. 7/contrib/PP-HumanSeg/README.md) 

2021

63. [KDD'21] Hao Liu*, Qian Gao*, Jiang Li, Xiaochao Liao, Hao Xiong, Guangxing Chen, Wenlin Wang, Guobao Yang, Zhiwei Zha, Daxiang Dong, Dejing Dou, and Haoyi Xiong^. JIZHI: A Fast and Cost-Effective Model-As-A-Service System for Web-Scale Online Inference at Baidu. The 27th SIGKDD Conference on Knowledge Discovery and Data Mining, Singapore, 2021.

64. [KDD'21] Shuangli Li,  Jingbo Zhou^,  Tong Xu,  Liang Huang,  Fan Wang, Haoyi Xiong, Weili  Huang,  Dejing Dou, and Hui  Xiong.   Structure-aware  Interactive  Graph Neural Networks for the Prediction of Protein-Ligand Binding Affinity.  The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Singapore, 2021.

65. [ICCV'21] Siyu Huang, Tianyang Wang, Haoyi Xiong, Jun Huan, and Dejing Dou. Semi-Supervised Active Learning with Temporal Output Discrepancy. International Conference on Computer Vision, 2021, IEEE/CVF.

66. [IJCAI'21] Xiao Zhang, Haoyi Xiong, and Dongrui Wu^.  Rethink the Connections among Generalization, Memorization, and the Spectral Bias of DNNs.  The 30th International Joint Conference on Artificial Intelligence, Online, 2021.

67. [AAAI'21] Congxi Xiao*, Jingbo Zhou*^, Jizhou Huang, An Zhuo, Ji Liu, Haoyi Xiong, and Dejing Dou. C-Watcher: A Framework for Early Detection of High-Risk Neighborhoods Ahead of COVID-19 Outbreak. Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, accepted, 2021.

68. [MLJ] Haiyan Jiang, Haoyi  Xiong^,  Dongrui  Wu,  Ji  Liu,  and  Dejing  Dou.   AgFlow: Accelerated  Model  Selection  for  Penalized  PCA  via  Gradient  Flow.   Machine Learning (for ECML’21 journal track), 2021, Springer.

69. [MLJ] Junjie Shi*^,Jiang Bian*, Jakob Richter, Kuan-Hsun Chen, Jorg Rahnenfuhrer, Haoyi Xiong, and Jian-Jia Chen. MODES: Model-based Optimization on Distributed Embedded Systems. Machine Learning (for ECML'21 journal track), 2021, Springer.

70. [KAIS] Sijia Yang, Haoyi Xiong, Di Hu, Kaibo Xu, Licheng Wang^, Peizhen Zhu, and Zeyi Sun^. Generalising Combinatorial Discriminant Analysis through Conditioning Truncated Rayleigh Flow. Knowledge and Information Systems, 2021, Springer.

71. [TKDD] Kafeng Wang*, Haoyi Xiong*^, Jiang Bian, Zhanxing Zhu, Qian Gao, Zhishan Guo, Cheng-Zhong Xu, and Jun Huan. Sampling Sparse Representations with Randomized Measurement Langevin Dynamics. ACM Transactions on Knowledge Discovery from Data, 2021 ACM. 

72. [TMM] Baoxin Zhao*, Haoyi Xiong*^,  Jiang Bian, Zhishan Guo, Cheng-zhong Xu, and Dejing Dou. COMO: Widening Deep Neural Networks with COnvolutional MaxOut. IEEE Transactions on Multimedia, 2021, IEEE. 

73. [T-ASE] Yunchao Zhang, Zeyi Sun^, Ruwen Qin, and Haoyi Xiong. Idle Duration Predictionfor Manufacturing System Using a Gaussian Mixture Model Integrated Neural Network for Energy Efficiency Improvement. IEEE Transactions on Automation Science and Engineering, 2021, IEEE. (Interdisciplinary Collaboration funded by Missouri S&T Smart CPS programs)

74. [CIKM'21] Chao Zhang, Jingbo Zhou^, Xiaoling Zang, Qing Xu, Liang Yin, Xiang He, Lin Liu, Haoyi Xiong, Dejing Dou. CHASE: Commonsense-Enriched Advertising on Search Engine with Explicit Knowledge. ACM International Conference on Knowledge and Information Management, 2021. 

75. [TIST] Xingjian Li*, Haoyi Xiong*^, Zeyu Chen, Jun Huan, Dejing Dou, and Cheng-Zhong Xu. In-Network Ensemble: Deep Ensemble Learning with Diversified Knowledge Distillation. ACM Transactions on Intelligent Systems and Technology, 2021, ACM.

76. [IOTJ] Kafeng Wang, Haoyi Xiong^, Jie Zhang, Hongyang Chen, Dejing Dou, and Cheng-Zhong Xu. SenseMag: Enabling Low-Cost Traffic Monitoring using Non-invasive Magnetic Sensing. IEEE Internet of Things Journal, 2021 IEEE.

2020

77. [ICML'20] Xingjian Li*^, Haoyi Xiong*^, Haozhe An, Dejing Dou, and Cheng-Zhong Xu. RIFLE: Backpropagation in Depth for Deep Transfer Learning through Re-Initializing the Fully-connected LayEr. International Conference on Machine Learning, Vienna, Austria, 2020. 

78. [ICML'20] Jingfeng Wu^, Wenqing Hu, Haoyi Xiong, Jun Huan, Vladimir Braverman, and Zhanxing Zhu^. On the Noisy Gradient Descent that Generalizes as SGD. International Conference on Machine Learning, Vienna, Austria, 2020

79. [IJCAI'20] Siyu Huang, Haoyi Xiong, Zhi-Qi Cheng, Qingzhong Wang, Xingran Zhou, Bihan Wen, Jun Huan, Dejing Dou. Generating Person Images with Appearance-aware Pose Stylization. the 29th International Joint Conference on Artificial Intelligence, Yokohama, Japan, 2020.

80. [AAAI'20] Jie An*, Haoyi Xiong*, Jiebo Luo, and Jun Huan . Ultrafast Photorealistic Style Transfer via Neural Architecture Search. In Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, accepted, NYC, 2020. (Oral presentation)

81. [TKDD] Jiang Bian*^, Haoyi Xiong*,  Yanjie Fu,  and Zhishan Guo. MP2SDA: Multi-Party Parallelized Sparse Discriminant Analysis. ACM Transactions on Knowledge Discovery from Data, 2020, ACM.

82. [BMVC'20] Qingzhong Wang, Jiuniu Wang, Antoni Chan, Siyu Huang, Haoyi Xiong, Xingjian Li, and Dejing Dou. Neighbours Matter: Image Captioning with Similar Images. British Machine Vision Conference, Manchester, United Kingdon, 2020.

83. Di Hu, Zheng Wang, Haoyi Xiong, Dong Wang, Feiping Nie, and Dejing Dou. Heterogeneous Scene Analysis via Self-supervised Audiovisual Learning. Workshop on Sight and Sound in IEEE/CVF Conference on Computer Vision and Pattern Recognition, Seattle, WA, 2020.

2019

84. [ICLR'19] Xingjian Li, Haoyi Xiong, Hanchao Wang, Yuxuan Rao, Liping Liu, and Jun Huan. DELTA: Deep Learning Transfer using Feature Map with Attention for Convolutional Neural Networks. In Proceedings of The Seventh International Conference on Learning Representations, New Orleans, LA, 2019.

85. [RTSS'19] Li Li*, Haoyi Xiong*^, Zhishan Guo^, Jun Wang, and Cheng-Zhong Xu. SmartPC: Hierarchical Pace Control in Real-Time Federated Learning System. In Proceedings of the the 40th IEEE Real-Time Systems Symposium, York, United Kingdom, 2020, IEEE.

86. [AAAI'19] Haoyi Xiong*^, Kafeng Wang*, Jiang Bian*, Zhanxing Zhu, Cheng-zhong Xu, Zhishan Guo, and Jun Huan. SpHMC: Spectral Hamiltonian Monte Carlo. In Proceedings of The Thirty-Third AAAI Conference on Artificial Intelligence, Honolulu, Hawaii, 2019. (*: Equal Contribution) 

87. [TNNLS] Yongliang Yang, Zhishan Guo, Haoyi Xiong, Yixin Yin, and Donald C. Wunsch^. Data-driven Robust Control of Discrete-Time Uncertain Linear Systems via Off-policy Reinforcement Learning. IEEE Transactions on Neural Networks and Learning Systems, 2019, IEEE.

88. [TNNLS] Haoyi Xiong^, Wei Cheng, Wenqing Hu, Jiang Bian, Zeyi Sun, and Zhishan Guo. DBSDA: Lowering the Bound of Misclassification Rate for Sparse Linear Discriminant Analysis via Model De-Biasing. IEEE Transactions on Neural Networks and Learning Systems, 2019, IEEE.

89. [Applied Energy] Rajkamal Kesharwani, Zeyi Sun^, Cihan Dagli, and Haoyi Xiong. Moving second generation biofuel manufacturing forward: Investigating economic viability and environmental sustainability considering two strategies for supply chain restructuring.  Applied Energy, pages 1467-1496, vol. 242., Elsevier, 2019. (top journal in Operations Research for energy policy, IF:8.42, Interdisciplinary Collaboration funded by Missouri S&T Smart CPS programs)

90. [ICDM'19] Ruosi Wan*, Haoyi Xiong*^, Xingjian Li, Zhanxing Zhu, and Jun Huan. Towards Making Deep Transfer Learning Never Hurt. Proceedings of the 19th IEEE International Conference on Data Mining, accepted, 2019.

91. [ECML/PKDD'19] Ruosi Wan, Mingjun Zhong, Haoyi Xiong and Zhanxing Zhu^. Neural Control Variates for Monte Carlo Variance Reduction. The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, accepted, 2019. 

92. [BigData'19] Zhi Feng*, Haoyi Xiong*^, Chuanyuan Song, Sijia Yang, Baoxin Zhao, Licheng Wang, Zeyu Chen, Liping Liu, and Jun Huan. SecureGBM: Secure Multi-Party Gradient Boosting. The 2019 IEEE International Conference on Big Data, Los Angeles, CA, 2019.

2018

93. [TMC] Jiangtao Wang, Yasha Wang^, Daqing Zhang, Feng Wang, Haoyi Xiong, Chao Chen and Qin Lv. Multi-Task Allocation in Mobile Crowd Sensing with Individual Task Quality Assurance. IEEE Transactions on Mobile Computing, vol 17 issue 9, 2018, IEEE.

94. [TMC] Liang Wang, Zhiwen Yu^, Qi Han, Bin Guo and Haoyi Xiong. Multi-objective Optimization based Allocation of Heterogeneous Spatial Crowdsourcing Tasks. IEEE Transactions on Mobile Computing, vol 17 issue 7, 2018, IEEE.

95. [RTSS'18]  Zhishan Guo, Kecheng Yang, Sudharsan Vaidhun, Samsil Arefin ,Sajal K. Das, and Haoyi Xiong^. Uniprocessor Mixed-Criticality Scheduling with Graceful Degradation by Completion Rate.  The 39th IEEE Real-Time Systems Symposium, Nashville, United States, 2018.

96. [IJCAI'18] Haoyi Xiong, Wei Cheng, Yanjie Fu, Jiang Bian, Wenqinghu and Zhishan Guo. De-biasing Covariance-Regularized Discriminant Analysis. the 27th International Joint Conference on Artificial Intelligence, Stockholm, Sweden, 2018

97. [AAAI'18] Jiang Bian*, Haoyi Xiong*^, Yanjie Fu and Sajal K Das. CSWA: Aggregation-Free Community Sensing. In Proceedings of The Thirty-Second AAAI Conference on Artificial Intelligence, New Orleans, United States, 2018. (*: Equal Contribution) 

98. [TECS] Ashikahmed Bhuiyan,  Abusayeed Saifullah, Nan Guan, Haoyi Xiong, Zhishan Guo^. Energy-Efficient Multi-Core Scheduling for Real-Time DAG Tasks. ACM Transactions on Embedded Computing Systems, 2018.

99. [ICDM'18] Xin Xu, Minghao Yin, Haoyi Xiong, Bo Jin, and Yanjie Fu. Dr. Right+: Embedding-based Adaptively-weighted Mixture Model for Finding Right Doctors with Healthcare Experience Data. Proceedings of the 18th IEEE International Conference on Data Mining, Singapore, 2018.

2017

100. [ComMag] Haoyi Xiong^, Daqing Zhang^, Zhishan Guo, Guanling Chen, and Laura E. Barnes. Near-Optimal Incentive Allocation for Piggyback Crowdsensing. IEEE Communications, 2017. (IF:10)

101. [ICDM'17] Haoyi Xiong, Wei Cheng, Jiang Bian, Wenqing Hu, and Zhishan Guo. AWDA: An Adaptive Wishart Discriminant Analysis. Proceedings of the 17th IEEE International Conference on Data Mining, New Orleans, United States, 2017

102. [ICDM'17] Jiang Bian, Haoyi Xiong^, Wei Cheng, Yanjie Fu, Wenqing Hu, and Zhishan Guo. Multi-Party Sparse Discriminant Learning. Proceedings of the 17th IEEE International Conference on Data Mining, 2017, New Orleans, United States, 2017

103. [ECRTS'17] Zhishan Guo, Ashikahmed Bhuiyan, Abusayeed Saifullah, Nan Guan, and Haoyi Xiong^. Energy-Efficient Multi-Core Scheduling for Real-Time DAG Tasks. Proceedings of the 29th Euromicro Conference on Real-Time Systems,  Croatia, 2017.

104. [TSMC] Leye Wang, Daqing Zhang^, Haoyi Xiong, J. Paul Gibson, Chao Chen and Bing Xie, ecoSense: Minimize Participants’ Total 3G Data Cost in Mobile Crowdsensing Using Opportunistic Relays. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2017.

105. [TIST] Leye Wang, Daqing Zhang^, Dingqi Yang, Animesh Pathak, Chao Chen, Xiao Han, Haoyi Xiong, Yasha Wang. SPACE-TA: Cost-Effective Task Allocation Exploiting Intra- and Inter-Data Correlations in Sparse Crowdsensing.  ACM Transactions on Intelligent Systems and Technology, v.9, i.2 , 2017.

106. [TIST] Haoyi Xiong, Jinghe Zhang, Yu Huang, Kevin Leach, and Laura E. Barnes^. Daehr: A Discriminant Analysis Framework for Electronic Health Record Data and an Application to Early Detection of Mental Health Disorders. ACM Transactions on Intelligent Systems and Technology, 2017.

107. [BHI'17] Jiang Bian, Laura E. Barnes, Guanling Chen, and Haoyi Xiong. Early detection of diseases using electronic health records data and covariance-regularized linear discriminant analysis. Proceedings of the 2017 IEEE EMBS International Conference on Biomedical & Health Informatics,  2017. 

2016 and Before

108. [TMC] Haoyi Xiong, Daqing Zhang^, Guanling Chen, Leye Wang, Vincent Gauthier, Laura E. Barnes, iCrowd: Near-Optimal Task Allocation for Piggyback Crowdsensing, IEEE Transactions on Mobile Computing, vol 15, issue 8, 2016. [Long Version]

109. [TMC] Haoyi Xiong, Daqing Zhang^, Leye Wang, Hakima Chaouchi, EMC3: Energy-efficient Data Transfer in Mobile Crowdsensing under Full Coverage Constraint, IEEE Transactions on Mobile Computing, vol.17, issue. 7, 2015. [PDF] [Appendix]

110. [UbiComp'16] Haoyi Xiong , Yu Huang, Laura E. Barnes and Matthew Gerber^, Sensus: A Cross-Platform and Context-Aware Crowdsensing Systems for Human-Subject Studies, The 2016 ACM International Joint Conference on Ubiquitous and Pervasive Computing. 

111. [UbiComp'16] Yu Huang* , Haoyi Xiong*, Kevin Leach, and Laura E. Barnes, Assessing Social Anxiety Using GPS Trajectories and Point-Of-Interest Data, The 2016 ACM International Joint Conference on Ubiquitous and Pervasive Computing, 2016. (*: Equal Contribution) 

112. [UbiComp'15] Leye Wang, Daqing Zhang^, Animesh Pathak, Chao Chen, Haoyi Xiong, Dingqi Yang and Yasha Wang. CCS-TA: Quality-Guaranteed Online Task Allocation in Compressive Crowdsensing. In Proc. of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing. 

113. [UbiComp'14] Daqing Zhang*,  Haoyi Xiong*, Leye Wang and Guanling Chen, CrowdRecruiter: Selecting Participants for Piggyback Crowdsensing under Probabilistic Coverage Constraint,  In Proc. of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing. (*: Equal Contribution)  [PDF] 

114. [PerCom'15] Haoyi Xiong, Daqing Zhang^, Guanling Chen, Leye Wang and Vincent Gauthier, CrowdTasker: Maximizing Coverage Quality in Piggyback Crowdsensing under Budget Constraint, In Proc. of the 13th IEEE International Conference on Pervasive Computing and Communications, St Louis, MO. (acceptance rate~15%)  [PDF] 

115. [NetMob'13] Haoyi Xiong, Leye Wang, Daqing Zhang. EEMC: An energy-efficient mobile crowdsensing mechanism by reusing Call/SMS connections, D4D Data Challenge, In Proc. of 2013 the main conference on the scientific analysis of mobile phone datasets, Cambridge, MA

116. Philip. I. Chow, Haoyi Xiong, Karl Fua, Wes Bonelli, Bethany Teachman, Laura E. Barnes, SAD: Social Anxiety and Depression Dynamic Monitoring System, Computing and Mental Health Worksop, ACM Conference on Human Factors in Computing Systems, San Jose, CA, 2016.

117. Leye Wang, Daqing Zhang and Haoyi Xiong, effSense: Energy-Efficient and Cost-Effective Data Uploading in Mobile Crowdsensing, Workshop on Pervasive Urban Crowdsensing Architecture and Applications with Ubicomp'13.

118. [UIC'12 Best Paper] Haoyi Xiong, Daqing Zhang^, Daqiang Zhang and Vincent Gauthier, Predicting Mobile Phone User Locations by Exploiting Collective Behavioral Patterns [slide], In Proc. of the 9th IEEE Conference on Ubiquitous Intelligence and Computing, Fukuoka, Japan, 2012. (Best Paper Award)

119. [TIST] Haoyi Xiong, Daqing Zhang^, Leye Wang, J.Paul Gibson and Jie Zhu, EEMC: Enabling Energy-efficient Mobile Crowd-sensing with Anonymous Participants, ACM Transactions on Intelligent Systems and Technology, vol. 6, issue. 3, 2015. [PDF]

120. [IOTJ] Jiangtao Wang, Yasha Wang^, Daqing Zhang, Leye Wang, Haoyi Xiong, Abdelsalam Helal, Yuanduo He, and Feng Wang. Fine-Grained Multitask Allocation for Participatory Sensing With a Shared Budget. IEEE Internet of Things Journal, 2016.

121. [TSMC] Leye Wang, Daqing Zhang^, Zhixian Yan, Haoyi Xiong and Bing Xie. effSense: A Novel Mobile Crowd-Sensing Framework for Energy-Efficient and Cost-Effective Data Uploading. IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 45, 2015.

122. [TC] Daqiang Zhang, Daqing Zhang^, Haoyi Xiong, Laurence T. Yang and Vincent Gauthier, NextCell: Predicting Location Using Social Interplay from Cell Phone Traces, IEEE Transactions on Computers, 2015.

123. [SIGCOMM'12] Daqiang Zhang, Athanasios V. Vasilakos, Haoyi Xiong. Predicting Location using Mobile Phone Calls (Poster). In Proc. of 2012 Annual Conference of the ACM Special Interest Group on Data Communication,  Helsinki, Finland, 2012.

124. [ComMag] Daqing Zhang^, Leye Wang, Haoyi Xiong and Bin Guo. 4W1H in Mobile Crowd Sensing. IEEE Communications, 2014.

125. [Network] Daqiang Zhang, Daqing Zhang^, Haoyi Xiong, Ching-Hsien Hsu and Athanasios Vasilakos, BASA: Building Mobile Ad-Hoc Social Networks on Top of Android, IEEE Network, 2014. 

126. [Wireless] Daqiang Zhang, Min Chen^, Mohsen Guizani, Haoyi Xiong and Daqing Zhang, Mobility Prediction in Telecom Cloud Using Mobile Calls, IEEE Wireless Communication, 2014.

127. [ISF Journal] Haoyi Xiong, Daqing Zhang^, Daqiang Zhang, Vincent Gauthier, Kun Yang and Monique Becker, MPaaS: Mobility Prediction as a Service in Telecom Cloud [slides], Information Systems Frontiers, 2014, Springer.