By Professor Lina Yao

Journal articles

Liu Y; Ye Z; Wang R; Li B; Sheng QZ; Yao L, 2024, 'Uncertainty-aware pedestrian trajectory prediction via distributional diffusion', Knowledge-Based Systems, 296, http://dx.doi.org/10.1016/j.knosys.2024.111862

Xu E; Zhao K; Yu Z; Zhang Y; Guo B; Yao L, 2024, 'Limits of predictability in top-N recommendation', Information Processing and Management, 61, http://dx.doi.org/10.1016/j.ipm.2024.103731

Yao L; McAuley J; Wang X; Jannach D, 2024, 'Special Issue on Responsible Recommender Systems Part 1', ACM Transactions on Intelligent Systems and Technology, http://dx.doi.org/10.1145/3663528

Fang XS; Wang X; Sheng QZ; Yao L, 2024, 'Generalizing truth discovery by incorporating multi-truth features', Computing, 106, pp. 1557 - 1583, http://dx.doi.org/10.1007/s00607-024-01288-9

Li N; Guo B; Liu Y; Ding Y; Yao L; Fan X; Yu Z, 2024, 'Hierarchical Constrained Variational Autoencoder for interaction-sparse recommendations', Information Processing and Management, 61, http://dx.doi.org/10.1016/j.ipm.2024.103641

Chen X; Wang S; McAuley J; Jannach D; Yao L, 2024, 'On the Opportunities and Challenges of Offline Reinforcement Learning for Recommender Systems', ACM Transactions on Information Systems, http://dx.doi.org/10.1145/3661996

Liu Y; Cui G; Luo J; Chang X; Yao L, 2024, 'Two-stream Multi-level Dynamic Point Transformer for Two-person Interaction Recognition', ACM Transactions on Multimedia Computing, Communications and Applications, 20, http://dx.doi.org/10.1145/3639470

Huang J; Ma B; Wang M; Zhou X; Yao L; Wang S; Qi L; Chen Y, 2024, 'Incentive Mechanism Design of Federated Learning for Recommendation Systems in MEC', IEEE Transactions on Consumer Electronics, 70, pp. 2596 - 2607, http://dx.doi.org/10.1109/TCE.2023.3342187

Liu Y; Li B; Wang X; Sammut C; Yao L, 2024, 'Attention-Aware Social Graph Transformer Networks for Stochastic Trajectory Prediction', IEEE Transactions on Knowledge and Data Engineering, http://dx.doi.org/10.1109/TKDE.2024.3390765

Yang C; Wang X; Yao L; Long G; Xu G, 2024, 'Dyformer: A dynamic transformer-based architecture for multivariate time series classification', Information Sciences, 656, http://dx.doi.org/10.1016/j.ins.2023.119881

Cao Y; Yao L; Pan L; Sheng QZ; Chang X, 2024, 'Guided Image-to-Image Translation by Discriminator-Generator Communication', IEEE Transactions on Multimedia, 26, pp. 1528 - 1538, http://dx.doi.org/10.1109/TMM.2023.3282869

Li Q; Wang Z; Xia H; Li G; Cao Y; Yao L; Xu G, 2024, 'HOT-GAN: Hilbert Optimal Transport for Generative Adversarial Network', IEEE Transactions on Neural Networks and Learning Systems, http://dx.doi.org/10.1109/TNNLS.2024.3370617

Li Z; Chen Y; Wang X; Yao L; Xu G, 2024, 'Multi-view GCN for loan default risk prediction', Neural Computing and Applications, http://dx.doi.org/10.1007/s00521-024-09695-x

Liu Z; Li Y; Yao L; Mcauley J; Dixon S, 2024, 'Rethink, Revisit, Revise: A Spiral Reinforced Self-Revised Network for Zero-Shot Learning', IEEE Transactions on Neural Networks and Learning Systems, 35, pp. 657 - 669, http://dx.doi.org/10.1109/TNNLS.2022.3176282

Ye Z; Yao L; Zhang Y; Gustin S, 2024, 'Self-supervised cross-modal visual retrieval from brain activities', Pattern Recognition, 145, http://dx.doi.org/10.1016/j.patcog.2023.109915

Liu Z; Li Y; Yao L; Chang X; Fang W; Wu X; Saddik AE, 2024, 'Simple Primitives With Feasibility- and Contextuality-Dependence for Open-World Compositional Zero-Shot Learning', IEEE Transactions on Pattern Analysis and Machine Intelligence, 46, pp. 543 - 560, http://dx.doi.org/10.1109/TPAMI.2023.3323012

Wang C; Chi CH; Yao L; Liew AWC; Shen H, 2023, 'Interdependence analysis on heterogeneous data via behavior interior dimensions', Knowledge-Based Systems, 279, http://dx.doi.org/10.1016/j.knosys.2023.110893

Chen X; Yao L; Wang X; Sun A; Sheng QZ, 2023, 'Generative Adversarial Reward Learning for Generalized Behavior Tendency Inference', IEEE Transactions on Knowledge and Data Engineering, 35, pp. 9878 - 9889, http://dx.doi.org/10.1109/TKDE.2022.3186920

Xu E; Yu Z; Li N; Cui H; Yao L; Guo B, 2023, 'Quantifying predictability of sequential recommendation via logical constraints', Frontiers of Computer Science, 17, http://dx.doi.org/10.1007/s11704-022-2223-1

Wang X; Yao L; Wang X; Paik HY; Wang S, 2023, 'Uncertainty Estimation With Neural Processes for Meta-Continual Learning', IEEE Transactions on Neural Networks and Learning Systems, 34, pp. 6887 - 6897, http://dx.doi.org/10.1109/TNNLS.2022.3215633

Xiao Y; Xing Z; Liu AX; Bai L; Pei Q; Yao L, 2023, 'Cure-GNN: A Robust Curvature-Enhanced Graph Neural Network Against Adversarial Attacks', IEEE Transactions on Dependable and Secure Computing, 20, pp. 4214 - 4229, http://dx.doi.org/10.1109/TDSC.2022.3211955

Chen X; Wang S; Qi L; Li Y; Yao L, 2023, 'Intrinsically motivated reinforcement learning based recommendation with counterfactual data augmentation', World Wide Web, 26, pp. 3253 - 3274, http://dx.doi.org/10.1007/s11280-023-01187-7

Li Z; Xu P; Chang X; Yang L; Zhang Y; Yao L; Chen X, 2023, 'When Object Detection Meets Knowledge Distillation: A Survey', IEEE Transactions on Pattern Analysis and Machine Intelligence, 45, pp. 10555 - 10579, http://dx.doi.org/10.1109/TPAMI.2023.3257546

Dong M; Yao L; Wang X; Xu X; Zhu L, 2023, 'Adversarial dual autoencoders for trust-aware recommendation', Neural Computing and Applications, 35, pp. 13065 - 13075, http://dx.doi.org/10.1007/s00521-021-05722-3

Tao Y; Wang C; Yao L; Li W; Yu Y, 2023, 'Item trend learning for sequential recommendation system using gated graph neural network', Neural Computing and Applications, 35, pp. 13077 - 13092, http://dx.doi.org/10.1007/s00521-021-05723-2

Xu E; Yu Z; Sun Z; Guo B; Yao L, 2023, 'Modeling Within-Basket Auxiliary Item Recommendation with Matchability and Ubiquity', ACM Transactions on Intelligent Systems and Technology, 14, http://dx.doi.org/10.1145/3574157

Yang C; Wang X; Yao L; Long G; Jiang J; Xu G, 2023, 'Attentional Gated Res2Net for Multivariate Time Series Classification', Neural Processing Letters, 55, pp. 1371 - 1395, http://dx.doi.org/10.1007/s11063-022-10944-0

Chen X; Yao L; McAuley J; Zhou G; Wang X, 2023, 'Deep reinforcement learning in recommender systems: A survey and new perspectives', Knowledge-Based Systems, 264, http://dx.doi.org/10.1016/j.knosys.2023.110335

MacIntyre CR; Chen X; Kunasekaran M; Quigley A; Lim S; Stone H; Paik HY; Yao L; Heslop D; Wei W; Sarmiento I; Gurdasani D, 2023, 'Artificial intelligence in public health: the potential of epidemic early warning systems', Journal of International Medical Research, 51, http://dx.doi.org/10.1177/03000605231159335

Zhang L; Chang X; Liu J; Luo M; Li Z; Yao L; Hauptmann A, 2023, 'TN-ZSTAD: Transferable Network for Zero-Shot Temporal Activity Detection', IEEE Transactions on Pattern Analysis and Machine Intelligence, 45, pp. 3848 - 3861, http://dx.doi.org/10.1109/TPAMI.2022.3183586

Altulyan M; Yao L; Kanhere S; Huang C, 2023, 'A blockchain framework data integrity enhanced recommender system', Computational Intelligence, 39, pp. 104 - 120, http://dx.doi.org/10.1111/coin.12548

Li C; Bai L; Yao L; Waller ST; Liu W, 2023, 'A bibliometric analysis and review on reinforcement learning for transportation applications', Transportmetrica B, 11, http://dx.doi.org/10.1080/21680566.2023.2179461

Li Y; Liu Z; Yao L; Chang X, 2023, 'Attribute-Modulated Generative Meta Learning for Zero-Shot Learning', IEEE Transactions on Multimedia, 25, pp. 1600 - 1610, http://dx.doi.org/10.1109/TMM.2021.3139211

Li Y; Liu Z; Yao L; Monaghan JJM; McAlpine D, 2023, 'Disentangled and Side-Aware Unsupervised Domain Adaptation for Cross-Dataset Subjective Tinnitus Diagnosis', IEEE Journal of Biomedical and Health Informatics, 27, pp. 538 - 549, http://dx.doi.org/10.1109/JBHI.2022.3225089

Li Y; Liu Z; Chang X; McAuley J; Yao L, 2023, 'Diversity-Boosted Generalization-Specialization Balancing for Zero-Shot Learning', IEEE Transactions on Multimedia, 25, pp. 8372 - 8382, http://dx.doi.org/10.1109/TMM.2023.3236211

Dong M; Yao L; Wang X; Benatallah B; Zhang S; Sheng QZ, 2023, 'Gradient Boosted Neural Decision Forest', IEEE Transactions on Services Computing, 16, pp. 330 - 342, http://dx.doi.org/10.1109/TSC.2021.3133673

Lou H; Ye Z; Yao L; Zhang Y, 2023, 'Less Is More: Brain Functional Connectivity Empowered Generalizable Intention Classification With Task-Relevant Channel Selection', IEEE Transactions on Neural Systems and Rehabilitation Engineering, 31, pp. 1888 - 1899, http://dx.doi.org/10.1109/TNSRE.2023.3252610

Wang S; Chen X; McAuley J; Cripps S; Yao L, 2023, 'Plug-and-Play Model-Agnostic Counterfactual Policy Synthesis for Deep Reinforcement Learning-Based Recommendation', IEEE Transactions on Neural Networks and Learning Systems, http://dx.doi.org/10.1109/TNNLS.2023.3329808

Li H; Feng CM; Xu Y; Zhou T; Yao L; Chang X, 2023, 'Zero-Shot Camouflaged Object Detection', IEEE Transactions on Image Processing, 32, pp. 5126 - 5137, http://dx.doi.org/10.1109/TIP.2023.3308295

Liu Y; Yao L; Li B; Sammut C; Chang X, 2022, 'Interpolation graph convolutional network for 3D point cloud analysis', International Journal of Intelligent Systems, 37, pp. 12283 - 12304, http://dx.doi.org/10.1002/int.23087

Zhu Y; Lian B; Wang Y; Miller C; Bales C; Fletcher J; Yao L; Waite TD, 2022, 'Machine learning modelling of a membrane capacitive deionization (MCDI) system for prediction of long-term system performance and optimization of process control parameters in remote brackish water desalination', Water Research, 227, http://dx.doi.org/10.1016/j.watres.2022.119349

Pelech T; Yao L; Saydam S, 2022, 'Planning lunar In-Situ Resource Utilisation with a reinforcement learning agent', Acta Astronautica, 201, pp. 401 - 419, http://dx.doi.org/10.1016/j.actaastro.2022.09.040

Zhang D; Yao L; Chen K; Yang Z; Gao X; Liu Y, 2022, 'Preventing Sensitive Information Leakage from Mobile Sensor Signals via Integrative Transformation', IEEE Transactions on Mobile Computing, 21, pp. 4517 - 4528, http://dx.doi.org/10.1109/TMC.2021.3078086

Li N; Guo B; Liu Y; Ding Y; Xu E; Yao L; Yu Z, 2022, 'Transfer how much: a fine-grained measure of the knowledge transferability of user behavior sequences in social network', Data Mining and Knowledge Discovery, 36, pp. 2214 - 2236, http://dx.doi.org/10.1007/s10618-022-00857-w

Wu B; Zhong L; Yao L; Ye Y, 2022, 'EAGCN: An Efficient Adaptive Graph Convolutional Network for Item Recommendation in Social Internet of Things', IEEE Internet of Things Journal, 9, pp. 16386 - 16401, http://dx.doi.org/10.1109/JIOT.2022.3151400

Dong M; Yuan F; Yao L; Wang X; Xu X; Zhu L, 2022, 'A survey for trust-aware recommender systems: A deep learning perspective', Knowledge-Based Systems, 249, http://dx.doi.org/10.1016/j.knosys.2022.108954

Altulyan M; Yao L; Wang X; Huang C; Kanhere SS; Sheng QZ, 2022, 'A Survey on Recommender Systems for Internet of Things: Techniques, Applications and Future Directions', Computer Journal, 65, pp. 2098 - 2132, http://dx.doi.org/10.1093/comjnl/bxab049

Li Y; Liu Z; Yao L; Wang X; McAuley J; Chang X, 2022, 'An Entropy-Guided Reinforced Partial Convolutional Network for Zero-Shot Learning', IEEE Transactions on Circuits and Systems for Video Technology, 32, pp. 5175 - 5186, http://dx.doi.org/10.1109/TCSVT.2022.3147902

Liu Z; Li Y; Yao L; Wang X; Nie F, 2022, 'Agglomerative Neural Networks for Multiview Clustering', IEEE Transactions on Neural Networks and Learning Systems, 33, pp. 2842 - 2852, http://dx.doi.org/10.1109/TNNLS.2020.3045932

Wang S; Cao Y; Chen X; Yao L; Wang X; Sheng QZ, 2022, 'Adversarial Robustness of Deep Reinforcement Learning Based Dynamic Recommender Systems', Frontiers in Big Data, 5, http://dx.doi.org/10.3389/fdata.2022.822783

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