By Professor Lina Yao

Journal articles

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

Yao L; Xu C; Zhang Y, 2023, 'Message from Program Chairs', Proceedings - 2023 International Conference on Artificial Intelligence of Things and Systems, AIoTSys 2023, pp. XIV, http://dx.doi.org/10.1109/AIoTSys58602.2023.00007

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

Chen K; Zhang D; Yao L; Guo B; Yu Z; Liu Y, 2022, 'Deep learning for sensor-based human activity recognition: Overview, challenges, and opportunities', ACM Computing Surveys, 54, http://dx.doi.org/10.1145/3447744

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

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, 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, 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, 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, 235, http://dx.doi.org/10.1016/j.knosys.2021.107665

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, 25, pp. 49 - 72, http://dx.doi.org/10.1007/s11280-021-00964-6

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, 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, 21, pp. 252 - 263, http://dx.doi.org/10.1109/TMC.2020.3005240

Li X; Yao L; Chen W, 2022, 'Preface', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 13726 LNAI, pp. v - vi

Li X; Yao L; Chen W, 2022, 'Preface', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 13725 LNAI, pp. v - vi

Fernández P; Medjahed B; Piattini M; Cortés AR; Yao L, 2022, 'Preface', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 13740 LNCS, pp. v - vi

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, 30, pp. 2352 - 2361, http://dx.doi.org/10.1109/TNSRE.2022.3201158

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, 34, http://dx.doi.org/10.1016/j.imu.2022.101121

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, 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, 13, 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, 131, pp. 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, 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, 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, 121, pp. 25 - 34, http://dx.doi.org/10.1016/j.future.2021.03.003

Guo B; Ding Y; Yao L; Liang Y; Yu Z, 2021, 'The Future of False Information Detection on Social Media: New Perspectives and Trends', ACM Computing Surveys, 53, http://dx.doi.org/10.1145/3393880

Zhang X; Yao L; Wang X; Monaghan J; Mcalpine D; Zhang Y, 2021, 'A survey on deep learning-based non-invasive brain signals: recent advances and new frontiers', Journal of Neural Engineering, 18, http://dx.doi.org/10.1088/1741-2552/abc902

Hao S; Guo B; Wang H; Liang Y; Yao L; Wang Q; Yu Z, 2021, 'DeepDepict: Enabling Information Rich, Personalized Product Description GenerationWith the Deep Multiple Pointer Generator Network', ACM Transactions on Knowledge Discovery from Data, 15, http://dx.doi.org/10.1145/3446982

Chen X; Yao L; Zhou T; Dong J; Zhang Y, 2021, 'Momentum contrastive learning for few-shot COVID-19 diagnosis from chest CT images', Pattern Recognition, 113, http://dx.doi.org/10.1016/j.patcog.2021.107826

Xiao Y; Pei Q; Xiao T; Yao L; Liu H, 2021, 'MutualRec: Joint friend and item recommendations with mutualistic attentional graph neural networks', Journal of Network and Computer Applications, 177, http://dx.doi.org/10.1016/j.jnca.2020.102954

Li C; Bai L; Liu W; Yao L; Waller ST, 2021, 'Urban mobility analytics: A deep spatial-temporal product neural network for traveler attributes inference', TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, 124, http://dx.doi.org/10.1016/j.tre.2020.102921

Li C; Bai L; Liu W; Yao L; Travis Waller S; Waller ST, 2021, 'Urban mobility analytics: A deep spatial–temporal product neural network for traveler attributes inference', Transportation Research Part C: Emerging Technologies, 124, pp. 102921, http://dx.doi.org/10.1016/j.trc.2020.102921

Shah SW; Kanhere SS; Zhang J; Yao L, 2021, 'VID: Human identification through vein patterns captured from commodity depth cameras', IET Biometrics, 10, pp. 142 - 162, http://dx.doi.org/10.1049/bme2.12009

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