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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
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 Web Information Systems Engineering – WISE 2022, Springer International Publishing, 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, Springer Singapore, 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, Springer International Publishing, 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, Springer International Publishing, 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, INST ENGINEERING TECH-IET, 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
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, vol. 17, http://dx.doi.org/10.1007/s11704-022-2223-1
Li Y; Liu Z; Chang X; McAuley J; Yao L, 2023, 'Diversity-Boosted Generalization-Specialization Balancing for Zero-Shot Learning', IEEE Transactions on Multimedia, pp. 1 - 11, http://dx.doi.org/10.1109/tmm.2023.3236211
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, vol. 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, vol. 227, pp. 119349, http://dx.doi.org/10.1016/j.watres.2022.119349
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, vol. 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, vol. 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, vol. 9, pp. 16386 - 16401, http://dx.doi.org/10.1109/JIOT.2022.3151400
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', The Computer Journal, vol. 65, pp. 2098 - 2132, http://dx.doi.org/10.1093/comjnl/bxab049
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, vol. 249, pp. 108954 - 108954, http://dx.doi.org/10.1016/j.knosys.2022.108954
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, vol. 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, vol. 33, pp. 2842 - 2852, http://dx.doi.org/10.1109/TNNLS.2020.3045932
Liu Z; Li Y; Yao L; McAuley J; Dixon S, 2022, 'Rethink, Revisit, Revise: A Spiral Reinforced Self-Revised Network for Zero-Shot Learning', IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, http://dx.doi.org/10.1109/TNNLS.2022.3176282
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, vol. 5, pp. 822783, http://dx.doi.org/10.3389/fdata.2022.822783
Chen X; Li Y; Yao L; Adeli E; Zhang Y; Wang X, 2022, 'Generative adversarial U-Net for domain-free few-shot medical diagnosis', Pattern Recognition Letters, vol. 157, pp. 112 - 118, http://dx.doi.org/10.1016/j.patrec.2022.03.022
Li Q; Yu Z; Yao L; Guo B, 2022, 'RLTIR: Activity-Based Interactive Person Identification via Reinforcement Learning Tree', IEEE Internet of Things Journal, vol. 9, pp. 4464 - 4475, http://dx.doi.org/10.1109/JIOT.2021.3104024
Salama U; Yao L; Paik HY, 2022, 'A Multilevel Collective Framework for Internet of Things Digital Forensic Investigation', Computer, vol. 55, pp. 44 - 53, http://dx.doi.org/10.1109/MC.2021.3095492
Liu Z; Wang X; Li Y; Yao L; An J; Bai L; Lim EP, 2022, 'Face to purchase: Predicting consumer choices with structured facial and behavioral traits embedding', Knowledge-Based Systems, vol. 235, http://dx.doi.org/10.1016/j.knosys.2021.107665
Altulyan M; Yao L; Kanhere S; Huang C, 2022, 'A blockchain framework data integrity enhanced recommender system', Computational Intelligence, http://dx.doi.org/10.1111/coin.12548
Li N; Guo B; Liu Y; Yao L; Liu J; Yu Z, 2022, 'AskMe: joint individual-level and community-level behavior interaction for question recommendation', World Wide Web, vol. 25, pp. 49 - 72, http://dx.doi.org/10.1007/s11280-021-00964-6
Yang C; Wang X; Yao L; Long G; Jiang J; Xu G, 2022, 'Attentional Gated Res2Net for Multivariate Time Series Classification', Neural Processing Letters, http://dx.doi.org/10.1007/s11063-022-10944-0
Li Y; Liu Z; Yao L; J.M.Monaghan J; McAlpine D, 2022, 'Disentangled and Side-Aware Unsupervised Domain Adaptation for Cross-Dataset Subjective Tinnitus Diagnosis', IEEE Journal of Biomedical and Health Informatics, http://dx.doi.org/10.1109/JBHI.2022.3225089
Chen X; Yao L; Wang X; Sun A; Sheng QZ, 2022, 'Generative Adversarial Reward Learning for Generalized Behavior Tendency Inference', IEEE Transactions on Knowledge and Data Engineering, http://dx.doi.org/10.1109/TKDE.2022.3186920
Huang C; Yao L; Wang X; Sheng QZ; Dustdar S; Wang Z; Xu X, 2022, 'Intent-Aware Interactive Internet of Things for Enhanced Collaborative Ambient Intelligence', IEEE Internet Computing, vol. 26, pp. 68 - 75, http://dx.doi.org/10.1109/MIC.2021.3099599
Chu J; Wang X; Qian K; Yao L; Xiao F; Li J; Yang Z, 2022, 'Passenger Demand Prediction with Cellular Footprints', IEEE Transactions on Mobile Computing, vol. 21, pp. 252 - 263, http://dx.doi.org/10.1109/TMC.2020.3005240
Liu Z; Li Y; Yao L; Lucas M; Monaghan JJM; Zhang Y, 2022, 'Side-Aware Meta-Learning for Cross-Dataset Listener Diagnosis With Subjective Tinnitus', IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 30, pp. 2352 - 2361, http://dx.doi.org/10.1109/TNSRE.2022.3201158
Zhang L; Chang X; Liu J; Luo M; Li Z; Yao L; Hauptmann A, 2022, 'TN-ZSTAD: Transferable Network for Zero-Shot Temporal Activity Detection', IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. PP, http://dx.doi.org/10.1109/TPAMI.2022.3183586
Wang X; Yao L; Wang X; Paik HY; Wang S, 2022, 'Uncertainty Estimation With Neural Processes for Meta-Continual Learning', IEEE Transactions on Neural Networks and Learning Systems, vol. PP, pp. 1 - 11, http://dx.doi.org/10.1109/TNNLS.2022.3215633
Zhang T; Rabhi F; Behnaz A; Chen X; Paik HY; Yao L; MacIntyre CR, 2022, 'Use of automated machine learning for an outbreak risk prediction tool', Informatics in Medicine Unlocked, vol. 34, pp. 101121 - 101121, http://dx.doi.org/10.1016/j.imu.2022.101121
Xiao Y; Xing Z; Liu AX; Bai L; Pei Q; Yao L, 2022, 'Cure-GNN: A Robust Curvature-Enhanced Graph Neural Network against Adversarial Attacks', IEEE Transactions on Dependable and Secure Computing, vol. PP, pp. 1 - 16, http://dx.doi.org/10.1109/tdsc.2022.3211955
Xu Y; Yin Y; Wang J; Wei J; Liu J; Yao L; Zhang W, 2021, 'Unsupervised Cross-View Feature Selection on incomplete data[Formula presented]', Knowledge-Based Systems, vol. 234, http://dx.doi.org/10.1016/j.knosys.2021.107595
Altulyan M; Yao L; Huang C; Wang X; Kanhere SS, 2021, 'Context-induced activity monitoring for on-demand things-of-interest recommendation in an ambient intelligent environment', Future Internet, vol. 13, pp. 305 - 305, http://dx.doi.org/10.3390/fi13120305
Li C; Bai L; Liu W; Yao L; Waller ST, 2021, 'A multi-task memory network with knowledge adaptation for multimodal demand forecasting', Transportation Research Part C: Emerging Technologies, vol. 131, pp. 103352 - 103352, http://dx.doi.org/10.1016/j.trc.2021.103352
Wang M; Chen W; Wang S; Jiang Y; Yao L; Qi G, 2021, 'Efficient search over incomplete knowledge graphs in binarized embedding space', Future Generation Computer Systems, vol. 123, pp. 24 - 34, http://dx.doi.org/10.1016/j.future.2021.04.006
Bouguettaya A; Sheng QZ; Benatallah B; Neiat AG; Mistry S; Ghose A; Nepal S; Yao L, 2021, 'An internet of things service roadmap', Communications of the ACM, vol. 64, pp. 86 - 95, http://dx.doi.org/10.1145/3464960
Bai L; Yao L; Wang X; Li C; Zhang X, 2021, 'Deep spatial–temporal sequence modeling for multi-step passenger demand prediction', Future Generation Computer Systems, vol. 121, pp. 25 - 34, http://dx.doi.org/10.1016/j.future.2021.03.003
Chen K; Zhang D; Yao L; Guo B; Yu Z; Liu Y, 2021, 'Deep learning for sensor-based human activity recognition: Overview, challenges, and opportunities', ACM Computing Surveys, vol. 54, pp. 1 - 40, http://dx.doi.org/10.1145/3447744