By Professor Lina Yao

Books

Zhang X; Yao L, 2021, Deep Learning for EEG-Based Brain–Computer Interfaces: Representations, Algorithms and Applications, http://dx.doi.org/10.1142/q0282

Sheng QZ; Qin Y; Yao L; Benatallah B, 2017, Managing the Web of Things: Linking the Real World to the Web

Sheng QZ; Qin Y; Yao L; Benatallah B, 2017, Preface, http://dx.doi.org/10.1016/B978-0-12-809764-9.00026-3

Yao L; Xie X; Zhang Q; Yang LT; Zomaya AY; Jin H, 2015, Preface

Book Chapters

Zhang S; Zhang A; Yao L, 2023, 'Recommender Systems', in Machine Learning for Data Science Handbook: Data Mining and Knowledge Discovery Handbook, Third Edition, pp. 637 - 658, http://dx.doi.org/10.1007/978-3-031-24628-9_28

Zhang S; Tay Y; Yao L; Sun A; Zhang C, 2022, 'Deep Learning for Recommender Systems', in Recommender Systems Handbook: Third Edition, pp. 173 - 210, http://dx.doi.org/10.1007/978-1-0716-2197-4_5

Li Z; Wang X; Yao L; Chen Y; Xu G; Lim EP, 2022, 'Graph Neural Network with Self-attention and Multi-task Learning for Credit Default Risk Prediction', in , pp. 616 - 629, http://dx.doi.org/10.1007/978-3-031-20891-1_44

Barukh MC; Zamanirad S; Baez M; Beheshti A; Benatallah B; Casati F; Yao L; Sheng QZ; Schiliro F, 2021, 'Cognitive Augmentation in Processes', in Next-Gen Digital Services. A Retrospective and Roadmap for Service Computing of the Future, pp. 123 - 137, http://dx.doi.org/10.1007/978-3-030-73203-5_10

Fang Z; Qu M; Zhang S; Zhang J; Yuan Y; Yao L; Chen S, 2021, 'HFM++: An Enhanced Holographic Factorization Machine for Recommendation', in Data Mining, pp. 72 - 85, http://dx.doi.org/10.1007/978-981-16-8531-6_6

Wang X; Yao L; Wang X; Nie F; Benatallah B, 2021, 'NP-PROV: Neural Processes with Position-Relevant-Only Variances', in Web Information Systems Engineering – WISE 2021, pp. 129 - 142, http://dx.doi.org/10.1007/978-3-030-90888-1_11

Chen X; Yao L; Zhang Y, 2021, 'RAU: An Interpretable Automatic Infection Diagnosis of COVID-19 Pneumonia with Residual Attention U-Net', in Web Information Systems Engineering – WISE 2021, pp. 122 - 136, http://dx.doi.org/10.1007/978-3-030-91560-5_9

Zhang S; Yao L; Sun A; Guo G; Xu X; Zhu L, 2019, 'Deep neural networks meet recommender systems', in Khalid O; Khan SU; Zomaya AY (ed.), Big Data Recommender Systems: Application Paradigms, pp. 9 - 33, http://dx.doi.org/10.1049/PBPC035G_ch2

Fang XS; Sheng QZ; Wang X; Barhamgi M; Yao L; Ngu AHH, 2018, 'Correction to: SourceVote: Fusing Multi-valued Data via Inter-source Agreements', in Conceptual Modeling, Springer International Publishing, pp. E1 - E1, http://dx.doi.org/10.1007/978-3-319-69904-2_40

Yao L; Sheng QZ; Ngu AHH; Li X; Benatallah B; Wang X, 2017, 'Building Entity Graphs for the Web of Things Management', in Managing the Web of Things: Linking the Real World to the Web, Elsevier, pp. 275 - 303, http://dx.doi.org/10.1016/B978-0-12-809764-9.00013-5

Yao L; Sheng QZ; Ngu AHH; Li X; Benatallah B; Wang X, 2017, 'Chapter 10 Building Entity Graphs for the Web of Things Management', in Managing the Web of Things, Elsevier, pp. 275 - 303, http://dx.doi.org/10.1016/b978-0-12-809764-9.00013-5

Sheng QZ; Qin Y; Yao L; Benatallah B, 2017, 'Preface', in Managing the Web of Things, Elsevier, pp. xvii - xviii, http://dx.doi.org/10.1016/b978-0-12-809764-9.00026-3

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

Back to profile page