Publications

Artificial General Intelligence

Conferences

1. Y. LiuY. SunJ.H. Lim. Counterfactual Dynamics Forecasting—a New Setting of Quantitative Reasoning. AAAI 2023 (oral).

2. S. Chen, H. Zhu, X. Chen, Y. Lei, T. Chen, G. Yu. End2End 3D Dense Captioning with Vote2Cap-DETR. Accepted, CVPR 2023.

3. Y. Feng, H. Zhu, D. Peng, X. Peng, P. Hu. RONO: Robust Discriminative Learning with Noisy Labels for 2D-3D Cross-Modal Retrieval. Accepted, CVPR 2023. 

4. L. Xu, M.H. Huang, X. Shang, Z. Yuan, Y. Sun, J. Liu. Meta Compositional Referring Expression Segmentation. Accepted, CVPR 2023. 

5. Xu Wong, Peng Hu, Ming Yan, Dezhong Peng: Correspondence-Free Domain Alignment for Unsupervised Cross-Domain Image Retrieval. AAAI 2023.

6. C. Ye, H. Zhu, Y. Liao, Y. Zhang, T. Chen, J. Fan. What Makes for Effective Few-shot Point Cloud Classification? Proceedings of the IEEE/CVF winter conference on applications of computer, 2022.

7. X. Yi, K. Tang, X.S. Hua, J.H. Lim, H. Zhang. Identifying Hard Noise in Long-Tailed Sample Distribution. ECCV 2022 (oral).

8. F. Fang, W. Liang, Y. Wu, Q. Xu, J.H. Lim. Improving Generalization of Reinforcement Learning Using a Bilinear Policy Network. IEEE ICIP 2022.

9. F. Fang, Q. Xu, J.H. Lim. Hierarchical Defect Detection Based On Reinforcement Learning. IEEE ICIP 2022.

10. Y.L. Tan, E.Y.K. Chew, A. Kong, J.J. Kim, J.H. Lim. Portmanteauing Features for Scene Text Recognition. IAPR ICPR 2022.

11. M.C. Leong, H. Zhang, H.L. Tan, L. Li, J.H. Lim. Combined CNN Transformer Encoder for Enhanced Fine-grained Human Action Recognition. IEEE CVPR 2022 Workshop on Fine-Grained Visual Categorization (FGVC9).

12. H. Fan, X. Chang, W. Zhang, Y. Cheng, Y. Sun, M. Kankanhalli. Self-supervised Global-Local Structure Modeling for Point Cloud Domain Adaptation With Reliable Voted Pseudo Labels. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2022: 6377-6386.

13. X. Sui, S. Li, X. Geng, Y. Wu, X. Xu, Y. Liu, R. Goh, H. Zhu. CRAFT: Cross-Attentional Flow Transformer for Robust Optical Flow. CVPR 2022.

14. Jiafei Duan, Samson Yu, Soujanya Poria, Bihan Wen, Cheston Tan: Pip: Physical Interaction Prediction via Mental Imagery with Span Selection. ECCV 2022, In Press.

15. Shantanu Jaiswal, Basura Fernando, Cheston TanTDAM: Top-Down Attention Module for Contextually Guided Feature Selection in CNNs. ECCV 2022, In Press.

16. Yunlu Chen, Basura Fernando, Hakan Bilen, Matthias Nießner, Efstratios Gavves: 3D Equivariant Graph Implicit Functions. ECCV 2022, In Press.

17. Kian Boon Koh, Basura Fernando: Consistency Regularization for Domain Adaptation. BMVC 2022, In Press.

18. Hehe Fan, Xiaojun Chang, Wanyue Zhang, Yi Cheng, Ying Sun, Mohan Kankanhalli: Self-Supervised Global-Local Structure Modeling for Point Cloud Domain Adaptation With Reliable Voted Pseudo Labels. CVPR 2022: 6377-6386.

19. Bowen Xing, Ivor W. Tsang: DARER: Dual-task Temporal Relational Recurrent Reasoning Network for Joint Dialog Sentiment Classification and Act Recognition. ACL 2022: 3611-3621.

20. Bowen Xing, Ivor W. Tsang: Neural Subgraph Explorer: Reducing Noisy Information via Target-oriented Syntax Graph Pruning. IJCAI 2022: 4425-4431.

21. Jiafei Duan, Arijit Dasgupta, Jason Fischer, Cheston Tan: A Survey on Machine Learning Approaches for Modelling Intuitive Physics. IJCAI 2022: 5444-5452.

22. Arushi Goel, Basura Fernando, Frank Keller, and Hakan Bilen: Not All Relations Are Equal: Mining Informative Labels for Scene Graph Generation. CVPR 2022: 15596-15606.

23. Cunlin Wu, Yang Xiao, Boshen Zhang, Mingyang Zhang, Zhiguo Cao, Joey Tianyi Zhou:C3P: Cross-domain Pose Prior Propagation for Weakly Supervised 3D Human Pose Estimation. ECCV 2022.

24. Chen Chen, Yufei Wang, Bing Li and Kwok-Yan Lam: Knowledge Is Flat: A Seq2Seq Generative Framework for Various Knowledge Graph Completion. COLING 2022: 4005 - 4017.

25. Jiawei Du, Daquan Zhou, Jiashi Feng, Vincent T.F. Tan, Joey Tianyi ZhouSharpness Aware-Training for Free. NeurIPS 2022.

26. Yuanbiao Gou, Peng Hu, Jiancheng Lv, Joey Tianyi Zhou, Xi Peng: Multi-Scale Adaptive Network for Single Image Denoising. NeurIPS 2022.

27. Linhan Zhang, Qian Chen, Wen Wang, Chong Deng, ShiLiang Zhang, Bing Li, Wei Wang, Xin Cao: MDERank: A Masked Document Embedding Rank Approach for Unsupervised Keyphrase Extraction. ACL 2022: 396 - 409.

28. Yunqiu Xu, Meng Fang, Ling Chen, Yali Du, Joey Tianyi Zhou, Chengqi Zhang: Perceiving the World: Question-guided Reinforcement Learning for Text-based Games. ACL 2022: 538 - 560.

29. Jiawei Du, Hanshu Yan, Jiashi Feng, Joey Tianyi Zhou, Liangli Zhen, Rick Siow Mong Goh, Vincent Y. F. Tan: Efficient Sharpness-aware Minimization for Improved Training of Neural Networks. ICLR 2022.

30. Philipp Bomatter, Mengmi Zhang, Dimitar Karev, Spandan Madan, Claire Tseng, Gabriel Kreiman: When Pigs Fly: Contextual Reasoning in Synthetic and Natural Scenes. ICCV 2021: 255-264.

31. Jiafei Duan, Samson Yu, Cheston Tan: Space: A Simulator for Physical Interactions and Causal Learning in 3D Environments. ICCV 2021: 2058-2063.

32. Qianli Xu, Nicolas Gauthier, Wenyu Liang, Fen Fang, Hui Li Tan, Ying Sun, Yan Wu, Liyuan Li, Joo-Hwee Lim: TAILOR: Teaching with Active and Incremental Learning for Object Registration. AAAI 2021: 16120-16123.

33. Shashi Kant Gupta, Mengmi Zhang, Chia-Chien Wu, Jeremy M. Wolfe, Gabriel Kreiman:
Visual Search Asymmetry: Deep Nets and Humans Share Similar Inherent Biases. NeurIPS 2021: 6946-6959.

34. Qianli Xu, Fen Fang, Ana Molino, Vigneshwaran Subbaraju, Joo-Hwee Lim: Predicting Event Memorability from Contextual Visual Semantics. NeurIPS 2021: 22431-22442.

35. Tiantian He, Yew Soon Ong, and Lu Bai: Learning Conjoint Attentions for Graph Neural Nets. NeurIPS 2021: 2641-2653.

36. Yueming Lyu, Ivor W. Tsang: Black-Box Optimizer with Stochastic Implicit Natural Gradient. ECML/PKDD 2021: 217-232.

37. Jinliang Deng, Xiusi Chen, Renhe Jiang, Xuan Song, Ivor W. Tsang: ST-Norm: Spatial and Temporal Normalization for Multi-variate Time Series Forecasting. KDD 2021: 269-278.

38. Yang Zhang, Ivor W. Tsang, Yawei Luo, Chang-Hui Hu, Xiaobo Lu, Xin Yu: Copy and Paste GAN: Face Hallucination From Shaded Thumbnails. CVPR 2020: 7353-7362.

39. Mengmi Zhang, Claire Tseng, Gabriel Kreiman: Putting Visual Object Recognition in Context. CVPR 2020: 12982-12991.

40. Maosen Li, Siheng Chen, Ya Zhang, Ivor W. Tsang: Graph Cross Networks with Vertex Infomax Pooling. NeurIPS 2020.

41. Yueming Lyu, Yuan Yuan, Ivor W. Tsang: Subgroup-based Rank-1 Lattice Quasi-Monte Carlo. NeurIPS 2020.

42. Xingrui Yu, Yueming Lyu, Ivor W. Tsang: Intrinsic Reward Driven Imitation Learning via Generative Model. ICML 2020: 10925-10935.

43. Han Tai, Raymond Wong and Bing Li: Effective Imbalance Learning Utilizing Informative Data. AusDM 2022: Data Mining 99–114.

44. Yongjie Wang, Hangwei Qian, Yongjie Liu, Wei Guo, Chunyan Miao. Flexible and Robust Counterfactual Explanations with Minimal Satisfiable Perturbations. CIKM 2023.

45. Qianwen Meng, Hangwei Qian, Yong Liu, Yonghui Xu, Zhiqi Shen and Lizhen Cui. MHCCL: Masked Hierarchical Cluster-wise Contrastive Learning for Multivariate Time Series. AAAI 2023: 37(8), 9153-9161.

46. Hangwei Qian, Tian Tian and Chunyan Miao. What Makes Good Contrastive Learning on Small-Scale Wearable-based Tasks?. KDD 2022: 3761–3771.

47. Chenyu Sun, Hangwei Qian and Chunyan Miao. CCLF: A Contrastive-Curiosity-Driven Learning Framework for Sample-Efficient Reinforcement Learning. IJCAI 2022: 3444-3450.

48. Yongjie Wang, Hangwei Qian, and Chunyan Miao. DualCF: Efficient Model Extraction Attack from Counterfactual Explanations. FAccT 2022: 1318–1329.

49. Fei Luo, Hangwei Qian, Di Wang, Xu Guo, Yan Sun, Eng Sing Lee, Hui Hwang Teong, Ray Tian Rui Lai and Chunyan Miao. Missing Value Imputation for Diabetes Prediction. IEEE WCCI 2022: 1-8.

50. Hangwei Qian, Sinno Jialin Pan and Chunyan Miao. Latent Independent Excitation for Generalisable Sensor-based Cross-Person Activity Recognition. AAAI 2021: 35(13), 11921-11929.

51. Hangwei Qian, Sinno Jialin Pan, Bingshui Da and Chunyan Miao. A Novel Distribution-Embedded Neural Network for Sensor-Based Activity Recognition. IJCAI 2019: 5614-5620.

52. Hangwei Qian, Sinno Jialin Pan and Chunyan Miao. Distribution-based Semi-Supervised Learning for Activity Recognition. AAAI 2019: 33(01), 7699-7706.

53. Hangwei Qian, Sinno Jialin Pan and Chunyan Miao. Sensor-based Activity Recognition via Learning from Distributions. AAAI 2018: 32(1).

54. Parantak Singh, You Li, Ankur Sikarwar, Weixian Lei, Daniel Gao, Morgan Bruce Talbot, Ying Sun, Mike Zheng Shou, Gabriel Kreiman, Mengmi Zhang. Learning to Learn: How to Continuously Teach Humans and Machines. ICCV 2023: 11708-11719.

55. Jay Zhangjie Wu, David Junhao Zhang, Wynne Hsu, Mengmi Zhang, Mike Zheng Shou. Label-efficient Online Continual Object Detection in Streaming Video. ICCV 2023: 19246-19255

56. Ankur Sikarwar, Mengmi ZhangDecoding the Enigma: Benchmarking Humans and AIs on the Many Facets of Working Memory. NeurIPS 2023.

57. Ren Jie Tee, Mengmi ZhangIntegrating Curricula with Replays: Its Effects on Continual Learning. AAAI 2023.

58. Zenglin Shi, Ying Sun, Mengmi Zhang. Training-free Object Counting with Prompts. WACV 2023.

59. Ziyu Wang, Mike Zheng Shou, Mengmi ZhangObject-centric Learning with Cyclic Walks between Parts and Whole. NeurIPS 2023.


Journals

1. Ye, C., Zhu, H., Zhang, B., Chen, T. "A Closer Look at Few-Shot 3D Point Cloud Classification." International Journal of Computer Vision, 131 (2023): 772–795.

2. Hu, P., Zhu, H., Lin, J., Peng, D., Zhao, Y.P., Peng, X. "Unsupervised Contrastive Cross-Modal Hashing." IEEE Transactions on Pattern Analysis and Machine Intelligence, 45(3): 3877 – 3889. (2023).

3. Liang, W., Fang, F., Acar, C., Toh, W.Q., Sun, Y., Xu, Q., Wu Y. "Visuo-Tactile Feedback-Based Robot Manipulation for Object Packing." IEEE Robotics & Automation Letters, 8(2): 1151 - 1158. (2023).

4. Koksal, A., Ak, K.E., Sun, Y., Rajan, D., Lim, J.H. "Controllable Video Generation with Text-based Instructions." Accepted, IEEE Transactions on Multimedia. (2023).

5. Ak, K.E., Sun, Y., Lim, J.H. "Learning by Imagination: A Joint Framework for Text-based Image Manipulation and Change Captioning.IEEE Transactions on Multimedia. (2022)

6. Fang, F., Xu, Q., Cheng, Y., Sun, Y., Lim, J.H. "Image Understanding with Reinforcement Learning: Auto-tuning Image Attributes and Model Parameters for Object Detection and Segmentation.IEEE Transactions on Circuits and Systems for Video Technology, 32(10): 6671-6685. (2022).

7. Fang, F., Liang, W., Wu, Y., Xu, Q., Lim, J.H. "Self-Supervised Reinforcement Learning for Active Object Detection." IEEE Robotics & Automation Letters, 7(4): 10224-10231. (2022). 

8. Cheng, Y., Sun Y., Fan, H., Zhuo, T., Lim, J.H., Kankanhalli, M. "Entropy Guided Attention Network for Weakly-supervised Action Localization." Pattern Recognition, 129. (2022).

9. Lew, L.W.C., Wang, D., Ang, K.K., Lim, J.H., Quek, C., Tan, A.H. "EEG-Video Emotion-based Summarization: Learning with EEG Auxiliary Signals." IEEE Transactions on Affective Computing, 13(4): 1827-1839. (2022).

10. Puang, E.Y, Zhang, H., Zhu, H., Jing, W. "Hierarchical Point Cloud Encoding and Decoding With Lightweight Self-Attention Based Model." IEEE Robotics and Automation Letters, 7 (2), 4542-4549. (2022).

11. Peng, X., Li, Y., Tsang, I.W., Zhu, H., Lv, J., Zhou, J.T.  "XAI Beyond Classification: Interpretable Neural Clustering." J. Mach. Learn. Res. 23, 6:1-6:28. (2022).

12. Mojtaba Shakeri, Erfan Miahi, Abhishek Gupta, and Yew-Soon Ong: "Scalable Transfer Evolutionary Optimization: Coping with Big Task-Instances." IEEE Transactions on Cybernetics, In Press, 2022.

13. Yinghua Yao, Yuangang Pan, Ivor W. Tsang, and Xin Yao: "Differential-Critic GAN: Generating What You Want by a Cue of Preferences.” IEEE Transactions on Neural Networks and Learning Systems, In Press, 2022.

14. Bowen Xing, and Ivor W. Tsang: "Out of Context: A New Clue for Context Modeling of Aspect-based Sentiment Analysis." Journal of Artificial Intelligent Research 74 (2022): 627-659.

15. Abhishek Gupta, Lei Zhou, Yew-Soon Ong, Zefeng Chen, and Yaqing Hou. "Half a Dozen Real-World Applications of Evolutionary Multitasking, and More." IEEE Computational Intelligence Magazine 17, no.2 (2022): 49-66.

16. Wong, Jian Cheng, Chinchun Ooi, Abhishek Gupta, and Yew-Soon Ong. "Learning in Sinusoidal Spaces with Physics-Informed Neural Networks." IEEE Transactions on Artificial Intelligence (2022).

17. Yi Cheng, Ying Sun, Hehe Fan, Tao Zhuo, Joo-Hwee Lim, and Mohan Kankanhalli. "Entropy Guided Attention Network for Weakly-supervised Action Localization." Pattern Recognition 129 (2022): 108718.

18. Jiafei Duan, Samson Yu, Hui Li Tan, Hongyuan Zhu, and Cheston Tan. "A Survey of Embodied AI: From Simulators to Research Tasks." IEEE Transactions on Emerging Topics in Computational Intelligence (2022).

19. Peiyao Zhao, Yuangang Pan, Xin Li, Xu Chen, Ivor W. Tsang, Lejian Liao. "Coarse-to-Fine Contrastive Learning on Graphs." IEEE Transactions on Neural Networks and Learning Systems (2022).

20. Yinghua Yao, Yuangang Pan*, Ivor W. Tsang, Xin Yao. "Differential-Critic GAN: Generating What You Want by a Cue of Preferences." IEEE Transactions on Neural Networks and Learning Systems (2022).

21. Heng Zhao, Joey Tianyi Zhou, Yew-Soon Ong. "Word2Pix: Word to Pixel Cross Attention Transformer in Visual Grounding." IEEE Transactions on Neural Networks and Learning Systems (2022).

22. Yang Zhang, Xin Yu, Xiaobo Lu, Ping Liu*(corresponding author). "Pro-UIGAN: Progressive Face Hallucination from Occluded Thumbnails." IEEE Transactions on Image processing (2022).

23. Yuangang Pan, Ivor W. Tsang*, Weijie Chen, Gang Niu, Masashi Sugiyama. "Fast and Robust Rank Aggregation against Model Misspecification." Journal of Machine Learning Research (2022).

24. Mengmi Zhang, and Kreiman Gabriel. "Beauty is in the Eye of the Machine." Nature Human Behaviour 5.6 (2021): 675-676.

25. Mitra Tajrobehkar, Kaihua Tang, Hanwang Zhang, and Joo-Hwee Lim. "Align R-CNN: A Pairwise Head Network for Visual Relationship Detection." IEEE Transactions on Multimedia 24 (2021): 1266-1276.

26. Jian Cheng Wong, Abhishek Gupta, and Yew-Soon Ong. "Can Transfer Neuro Evolution Tractably Solve your Differential Equations?" IEEE Computational Intelligence Magazine 16, no. 2 (2021): 14-30.

27. Lu Bai, Wu Lin, Abhishek Gupta, and Yew-Soon Ong. "From Multitask Gradient Descent to Gradient-free Evolutionary Multitasking: A Proof of Faster Convergence." IEEE Transactions on Cybernetics (2021).

28. Xiaofeng Cao, and Ivor W. Tsang. "Distribution Disagreement via Lorentzian Focal Representation." IEEE Transactions on Pattern Analysis and Machine Intelligence (2021).

29. Yang Zhang, Ivor W. Tsang, Yawei Luo, Changhui Hu, Xiaobo Lu, and Xin Yu. "Recursive Copy and Paste GAN: Face Hallucination from Shaded Thumbnails." IEEE Transactions on Pattern Analysis and Machine Intelligence 44, no. 8 (2021): 4321-4338.

30. Weiwei Liu, Haobo Wang, Xiaobo Shen, and Ivor W. Tsang. "The Emerging Trends of Multi-label Learning." IEEE Transactions on Pattern Analysis and Machine Intelligence (2021).

31. Xiaofeng Cao, and Ivor W. Tsang. "Distribution Disagreement via Lorentzian Focal Representation." IEEE Transactions on Pattern Analysis and Machine Intelligence (2021).

32. Xiaofeng Xu, Ivor W. Tsang, and Chuancai Liu. "Improving Generalization via Attribute Selection on Out-of-the-Box Data." Neural Computation 32, no. 2 (2020): 485-514.

33. Yaxin Shi, Yuangang Pan, Donna Xu, and Ivor W. Tsang. "Multiview Alignment and Generation in CCA via Consistent Latent Encoding." Neural Computation 32, no. 10 (2020): 1936-1979.

34. Mengmi Zhang, Jiashi Feng, Keng Teck Ma, Joo Hwee Lim, Qi Zhao, and Gabriel Kreiman. "Finding Any Waldo with Zero-shot Invariant and Efficient Visual Search." Nature Communications 9.1 (2018): 1-15.

35. Peiyao Zhao, Yuangang Pan, Xin Li, Xu Chen, Ivor Tsang, Lejian Liao. "Coarse-to-Fine Contrastive Learning on Graphs.IEEE Transactions on Neural Networks and Learning Systems (2022).

36. Hangwei Qian, Sinno Jialin Pan and Chunyan Miao. "Weakly-Supervised Sensor-based Activity Segmentation and Recognition via Learning from Distributions." Artificial Intelligence Journal (2021).


Resilient & Safe AI

Conferences

1. Alvin Chan, Yew Soon Ong, Clement Tan: How Does Frequency Bias Affect the Robustness of Neural Image Classifiers against Common Corruption and Adversarial Perturbations? IJCAI 2022: 659-665.

2. Zhiwei Hu, Victor Gutiérrez-Basulto, Zhiliang Xiang, Xiaoli Li, Ru Li, Jeff Z. Pan: Type-aware Embeddings for Multi-Hop Reasoning over Knowledge Graphs. IJCAI 2022: 3078-3084.

3. Sebastian Shenghong Tay, Chuan Sheng Foo, Urano Daisuke, Richalynn Leong, Bryan Kian Hsiang Low: Efficient Distributionally Robust Bayesian Optimization with Worst-case Sensitivity. ICML 2022: 21180-21204.

4. Xinghua Qu, Pengfei Wei, Mingyong Gao, Zhu Sun, Yew Soon Ong, Zejun Ma: Synthesising Audio Adversarial Examples for Automatic Speech Recognition. KDD 2022: 1430-1440.

5. Xinghua Qu, Yew Soon Ong, Abhishek Gupta, Pengfei Wei, Zhu Sun, Zejun Ma: Importance Prioritized Policy Distillation. KDD 2022: 1420-1429.

6. Kangkang Lu, Cuong Manh Nguyen, Xun Xu, Kiran Chari, Yu Jing Goh, Chuan-Sheng FooARMOURED: Adversarially Robust MOdels using Unlabeled data by REgularizing Diversity. ICLR 2021.

7. Xiaofeng Fan, Yining Ma, Zhongxiang Dai, Wei Jing, Cheston Tan, Bryan Kian Hsiang Low: Fault-Tolerant Federated Reinforcement Learning with Theoretical Guarantee. NeurIPS 2021: 1007-1021.

8. Jiawei Du, Hu Zhang, Joey Tianyi Zhou, Yi Yang, Jiashi Feng: Query-efficient Meta Attack to Deep Neural Networks. ICLR 2020.

9. Di Jin, Zhijing Jin, Joey Tianyi Zhou, Peter Szolovits: Is BERT Really Robust? A Strong Baseline for Natural Language Attack on Text Classification and Entailment. AAAI 2020: 8018-8025.

10. Yueming Lyu, Ivor W. Tsang: Curriculum Loss: Robust Learning and Generalization against Label Corruption. ICLR 2020.

11. Bo Han, Gang Niu, Xingrui Yu, Quanming Yao, Miao Xu, Ivor W. Tsang, Masashi Sugiyama: SIGUA: Forgetting May Make Learning with Noisy Labels More Robust. ICML 2020: 4006-4016. 

12. Houssam Zenati, Manon Romain, Chuan-Sheng Foo, Bruno Lecouat, Vijay Chandrasekhar: Adversarially Learned Anomaly Detection. ICDM 2018: 727-736.

13. Ping Liu, Xin Yu, Joey Tianyi ZhouMeta Knowledge Condensation for Federated Learning. ICLR 2023.

Journals

1. Yuangang Pan, Ivor W. Tsang, Weijie Chen, Gang Niu, and Masashi Sugiyama. "Fast and Robust Rank Aggregation against Model Misspecification." Journal of Machine Learning Research 23 (2022): 23-1.

2. Xi Peng, Yunfan Li, Ivor W. Tsang, Hongyuan Zhu, Jiancheng Lv, and Joey Tianyi Zhou. "XAI Beyond Classification: Interpretable Neural Clustering." Journal of Machine Learning Research 23 (2022): 6-1.

3. Zongbo Han, Changqing Zhang, Huazhu Fu, and Joey Tianyi Zhou. "Trusted Multi-View Classification with Dynamic Evidential Fusion." IEEE Transactions on Pattern Analysis and Machine Intelligence (2022).

4. Astha Garg, Wenyu Zhang, Jules Samaran, Ramasamy Savitha, and Chuan-Sheng Foo. "An Evaluation of Anomaly Detection and Diagnosis in Multivariate Time Series." IEEE Transactions on Neural Networks and Learning Systems 33, no. 6 (2021): 2508-2517.

5. Yuangang Pan, Ivor W. Tsang, Yueming Lyu, Avinash K. Singh, and Chin-Teng Lin. "Online Mental Fatigue Monitoring via Indirect Brain Dynamics Evaluation." Neural Computation 33, no. 6 (2021): 1616-1655.

6. Xinghua Qu, Yew-Soon Ong, and Abhishek Gupta. "Frame-correlation Transfers Trigger Economical Attacks on Deep Reinforcement Learning Policies." IEEE Transactions on Cybernetics (2021).

7. Xinghua Qiu, Abhishek Gupta, Yew-Soon Ong, and Zhu Sun. "Adversary Agnostic Robust Deep Reinforcement Learning." IEEE Transactions on Neural Networks and Learning Systems (2021).

8. Zhang, Le, Wei Cui, Bing Li*, Zhenghua Chen, Min Wu, and Teo Sin Gee. "Privacy-Preserving Cross-Environment Human Activity Recognition." IEEE Transactions on Cybernetics (2021): 1 - 11.

9. Xu Chen, Siheng Chen, Jiangchao Yao, Huangjie Zheng, Ya Zhang, and Ivor W. Tsang. "Learning on Attribute-missing Graphs." IEEE Transactions on Pattern Analysis and Machine Intelligence (2020).

10. Huiting Hong, Xin Li, Yuangang Pan, and Ivor Tsang. "Domain-adversarial Network Alignment." IEEE Transactions on Knowledge and Data Engineering (2020).

11. Xiaofeng Cao, and Ivor W. Tsang. "Shattering Distribution for Active Learning." IEEE Transactions on Neural Networks and Learning Systems (2020).

12. Bo Han, Ivor W. Tsang, Xiaokui Xiao, Ling Chen, Sai-Fu Fung, and P. Yu Celina. "Privacy-preserving Stochastic Gradual Learning." IEEE Transactions on Knowledge and Data Engineering 33, no. 8 (2020): 3129-3140.

13. Yuangang Pan, Ivor W. Tsang, Avinash K. Singh, Chin-Teng Lin, and Masashi Sugiyama. "Stochastic Multichannel Ranking with Brain Dynamics Preferences." Neural Computation 32, no. 8 (2020): 1499-1530.

14. Yanxin Zhang, Yulei Sui, Shirui Pan, Zheng Zheng, Baodi Ning, Ivor W. Tsang, and Wanlei Zhou. "Familial Clustering for Weakly-labeled Android Malware Using Hybrid Representation Learning." IEEE Transactions on Information Forensics and Security 15 (2019): 3401-3414.

15. Jing Li, Yuangang Pan, Yulei Sui, and Ivor W. Tsang. "Secure Metric Learning via Differential Pairwise Privacy." IEEE Transactions on Information Forensics and Security 15 (2020): 3640-3652.

16. Defu Liu; Ivor W. Tsang, Guowu Yang. “A Convergence Path to Deep Learning on Noisy Labels." IEEE Transactions on Neural Networks and Learning Systems. In Press.

Sustainable AI

Conferences

1. Wenyu Zhang, Li Shen, Wanyue Zhang, Chuan-Sheng Foo: Few-shot Adaptation of Pre-trained Networks for Domain Shift. IJCAI 2022: 1665-1671.

2. Yuecong Xu, Jianfei Yang, Haozhi Cao, Keyu Wu, Min Wu, and Zhenghua ChenLearning Temporal Consistency for Source-Free Video Domain Adaptation. ECCV 2022.

3. Keyu Wu, Min Wu, Zhenghua Chen, Yuecong Xu, Xiaoli Li: Generalising Reinforcement Learning through Fusing Self-Supervised Learning into Intrinsic Motivation. AAAI 2022.

4. Aye Phyu Phyu Aung, Xinrun Wang, Runsheng Yu, Bo An, Senthilnath Jayavelu, Xiaoli LiDO-GAN: A Double Oracle Framework for Generative Adversarial Networks. CVPR 2022: 11275-11284.

5. Yuxiang Zhang, Tao Jiang, Tianyu Yang, Xiaoli Li, and Suge Wang: HTKG: Deep Keyphrase Generation with Neural Hierarchical Topic Guidance. SIGIR 2022: 1044–1054.

6. Zhiwei Hu, Victor Gutierrez Basulto, Zhiliang Xiang, Xiaoli Li, Ru Li, Jeff Z. Pan: TEMP: Type-aware Embeddings for Multi-Hop Reasoning over Knowledge Graphs. IJCAI 2022.

7. Xu Wong, Peng Hu, Ming Yan, Dezhong Peng: Correspondence-Free Domain Alignment for Unsupervised Cross-Domain Image Retrieval. AAAI 2023.

8. Bing Li, Wei Cui, Yanru Chen, Joey Tianyi Zhou, Zhenghua Chen, Yuli Li, Wu Min: Cost-Effective Elderly Fall Detection with Symmetry Transformer Networks. IEEE SmartCity 2022.

Journals 

1. Yang He, Ping Liu, Linchao Zhu, and Yi Yang. "Filter Pruning by Switching to Neighboring CNNs with Good Attributes." IEEE Transactions on Neural Networks and Learning Systems (2022).

2. Zhehui Wang, Tao Luo, Rick Siow Mong Goh, and Joey Tianyi Zhou. "EDCompress: Energy-aware Model Compression for Dataflows." IEEE Transactions on Neural Networks and Learning Systems (2022).

3. Tian Huang, Tao Luo, Ming Yan and Joey Tianyi Zhou, and Rick Siow Mong Goh. “RCT: Resource Constrained Training for Edge AI." IEEE Transactions on Neural Networks and Learning Systems (2022).

4. Zhenghua Chen, Min Wu, Alvin Chan, Xiaoli Li, and Yew-Soon Ong. "A Survey on AI Sustainability: Emerging Trends on Learning Algorithms and Research Challenges." arXiv preprint arXiv:2205.03824 (2022).

5. Mohamed Ragab, Emadeldeen Eldele, Zhenghua Chen, Min Wu, Chee-Keong Kwoh, and Xiaoli Li. "Self-supervised Autoregressive Domain Adaptation for Time Series Data." IEEE Transactions on Neural Networks and Learning Systems (2022).

6. Jiaqi Xu, Yuanwei Liu, Xidong Mu, Joey Tianyi Zhou, Lingyang Song, H. Vincent Poor, and Lajos Hanzo. "Simultaneously Transmitting and Reflecting Intelligent Omni-surfaces: Modeling and Implementation." IEEE Vehicular Technology Magazine 17, no. 2 (2022): 46 - 54.

7. Tian Huang, Tao Luo, Ming Yan and Joey Tianyi Zhou, Rick Siow Mong Goh. "RCT: Resource Constrained Training for Edge AI." IEEE Transactions on Neural Networks and Learning Systems (2022).

8. Zhehui Wang, Tao Luo, Rick Siow Mong Goh, and Joey Tianyi Zhou. "Efficient Spiking Neural Networks with Radix Encoding." IEEE Transactions on Neural Networks and Learning Systems (2022).

9. Yang He, Ping Liu, Linchao Zhu, and Yi Yang. "Filter Pruning by Switching to Neighboring CNNs with Good Attributes." IEEE Transactions on Neural Networks and Learning Systems (2022).

10. Xiaodong Wang, Zhedong Zheng, Yang He, Fei Yan, Zhiqiang Zeng, Yi Yang. "Soft Person Reidentification Network Pruning via Blockwise Adjacent Filter Decaying." IEEE Transactions on Cybernetics 52, no. 12 (2021): 13293 - 13307.

11. Qing Xu, Zhenghua Chen, Keyu Wu, Chao Wang, Min Wu, and Xiaoli Li. "KDnet-RUL: A Knowledge Distillation Framework to Compress Deep Neural Networks for Machine Remaining Useful Life Prediction." IEEE Transactions on Industrial Electronics 69, no. 2 (2021): 2022-2032.

12. Pan Lai, Rui Fan, Xiao Zhang, Wei Zhang, Fang Liu, and Joey Tianyi Zhou. "Utility Optimal Thread Assignment and Resource Allocation in Multi-server Systems." IEEE/ACM Transactions on Networking 30, no. 2 (2021): 735-748.

13. Joey Tianyi Zhou, Heng Zhao, Xi Peng, Meng Fang, Zheng Qin, and Rick Siow Mong Goh. "Transfer Hashing: From Shallow to Deep." IEEE Transactions on Neural Networks and Learning Systems 29, no. 12 (2018): 6191-6201.

14. Hao Cheng, Joey Tianyi Zhou, Wee Peng Tay, Bihan Wen. "Graph Neural Networks with Triple Attention for Few-Shot Learning." IEEE Transactions on Multimedia (2022).

15. Tao Qiu, Chuanyu Zong, Xiaochun Yang, Bin Wang, Bing Li." Hierarchical Filtering: Improving Similar Substring Matching Under Edit Distance. World Wide Web (2022).

Others

Few-Shot Adaptation of Pre-Trained Networks for Domain Shift
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A Survey on Machine Learning Approaches for Modelling Intuitive Physics
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A Survey of Embodied Al: From Simulators to Research Tasks
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Simultaneously Transmitting and Reflecting (STAR)-RISs: Are They Applicable to Dual-Sided Incidence?
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Simultaneously Transmitting and Reflecting Intelligent Omni-Surfaces: Modeling and Implementation
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