By Professor Lina Yao

Preprints

Liu Y; Sheng QZ; Yao L, 2024, Modeling Pedestrian Intrinsic Uncertainty for Multimodal Stochastic Trajectory Prediction via Energy Plan Denoising, , http://dx.doi.org/10.48550/arxiv.2405.07164

Chen X; Wang S; McAuley J; Jannach D; Yao L, 2023, On the Opportunities and Challenges of Offline Reinforcement Learning for Recommender Systems, , http://dx.doi.org/10.48550/arxiv.2308.11336

Liu Y; Cui G; Luo J; Chang X; Yao L, 2023, Two-stream Multi-level Dynamic Point Transformer for Two-person Interaction Recognition, , http://dx.doi.org/10.48550/arxiv.2307.11973

Wang S; Chen X; Jannach D; Yao L, 2023, Causal Decision Transformer for Recommender Systems via Offline Reinforcement Learning, , http://dx.doi.org/10.48550/arxiv.2304.07920

Wang S; Chen X; Sheng QZ; Zhang Y; Yao L, 2023, Causal Disentangled Variational Auto-Encoder for Preference Understanding in Recommendation, , http://dx.doi.org/10.48550/arxiv.2304.07922

Li Z; Chen Y; Wang X; Yao L; Xu G, 2023, Multi-view GCN for Loan Default Risk Prediction, , http://dx.doi.org/10.21203/rs.3.rs-2754272/v1

Liu Y; Ye Z; Wang R; Li B; Sheng QZ; Yao L, 2023, Uncertainty-Aware Pedestrian Trajectory Prediction via Distributional Diffusion, , http://dx.doi.org/10.48550/arxiv.2303.08367

Cao Y; Yao L; Pan L; Sheng QZ; Chang X, 2023, Guided Image-to-Image Translation by Discriminator-Generator Communication, , http://dx.doi.org/10.48550/arxiv.2303.03598

Li C; Bai L; Yao L; Waller ST; Liu W, 2022, A Bibliometric Analysis and Review on Reinforcement Learning for Transportation Applications, , http://dx.doi.org/10.48550/arxiv.2210.14524

Chen X; Wang S; Yao L; Qi L; Li Y, 2022, Intrinsically Motivated Reinforcement Learning based Recommendation with Counterfactual Data Augmentation, , http://dx.doi.org/10.48550/arxiv.2209.08228

Wang S; Chen X; Yao L; Cripps S; McAuley J, 2022, Plug-and-Play Model-Agnostic Counterfactual Policy Synthesis for Deep Reinforcement Learning based Recommendation, , http://dx.doi.org/10.48550/arxiv.2208.05142

Soltani B; Haghighi V; Mahmood A; Sheng QZ; Yao L, 2022, A Survey on Participant Selection for Federated Learning in Mobile Networks, , http://dx.doi.org/10.48550/arxiv.2207.03681

Li C; Bai L; Liu W; Yao L; Waller ST, 2022, Unsupervised Knowledge Adaptation for Passenger Demand Forecasting, , http://dx.doi.org/10.48550/arxiv.2206.04053

Li Y; Liu Z; Yao L; Monaghan JJM; McAlpine D, 2022, Disentangled and Side-aware Unsupervised Domain Adaptation for Cross-dataset Subjective Tinnitus Diagnosis, , http://dx.doi.org/10.48550/arxiv.2205.03230

Li Y; Liu Z; Yao L; Lucas M; Monaghan JJM; Zhang Y, 2022, Side-aware Meta-Learning for Cross-Dataset Listener Diagnosis with Subjective Tinnitus, , http://dx.doi.org/10.48550/arxiv.2205.03231

Wang S; Cao Y; Chen X; Yao L; Wang X; Sheng QZ, 2021, Adversarial Robustness of Deep Reinforcement Learning based Dynamic Recommender Systems, , http://dx.doi.org/10.48550/arxiv.2112.00973

Liu Z; Li Y; Yao L; McAuley J; Dixon S, 2021, Rethink, Revisit, Revise: A Spiral Reinforced Self-Revised Network for Zero-Shot Learning, , http://arxiv.org/abs/2112.00410v1

Chen X; Yao L; Wang X; McAuley J, 2021, Locality-Sensitive Experience Replay for Online Recommendation, , http://dx.doi.org/10.48550/arxiv.2110.10850

Chen X; Yao L; Wang X; Sun A; Zhang W; Sheng QZ, 2021, Generative Adversarial Reward Learning for Generalized Behavior Tendency Inference, , http://dx.doi.org/10.48550/arxiv.2105.00822

Bouguettaya A; Sheng QZ; Benatallah B; Neiat AG; Mistry S; Ghose A; Nepal S; Yao L, 2021, An Internet of Things Service Roadmap, , http://dx.doi.org/10.48550/arxiv.2103.03043

Li C; Bai L; Liu W; Yao L; Waller ST, 2020, Knowledge Adaption for Demand Prediction based on Multi-task Memory Neural Network, , http://dx.doi.org/10.48550/arxiv.2009.05777

Liu Z; Yao L; Bai L; Wang X; Wang C, 2020, Spectrum-Guided Adversarial Disparity Learning, , http://dx.doi.org/10.1145/3394486.3403054

Altulyan M; Yao L; Wang X; Huang C; Kanhere SS; Sheng QZ, 2020, Recommender Systems for the Internet of Things: A Survey, , http://dx.doi.org/10.48550/arxiv.2007.06758

Wang X; Yao L; Wang X; Nie F, 2020, NP-PROV: Neural Processes with Position-Relevant-Only Variances, , http://dx.doi.org/10.48550/arxiv.2007.00767

Cao Y; Chen X; Yao L; Wang X; Zhang WE, 2020, Adversarial Attacks and Detection on Reinforcement Learning-Based Interactive Recommender Systems, , http://dx.doi.org/10.48550/arxiv.2006.07934

Liu Z; Li Y; Yao L; Wang X; Nie F, 2020, Agglomerative Neural Networks for Multi-view Clustering, , http://arxiv.org/abs/2005.05556v1

Tran DH; Sheng QZ; Zhang WE; Hamad SA; Zaib M; Tran NH; Yao L; Khoa NLD, 2020, Deep Conversational Recommender Systems: A New Frontier for Goal-Oriented Dialogue Systems, , http://dx.doi.org/10.48550/arxiv.2004.13245

Liu Z; Yao L; Wang X; Bai L; An J, 2020, Are You A Risk Taker? Adversarial Learning of Asymmetric Cross-Domain Alignment for Risk Tolerance Prediction, , http://dx.doi.org/10.1109/IJCNN48605.2020.9207111

Chen X; Huang C; Yao L; Wang X; Liu W; Zhang W, 2020, Knowledge-guided Deep Reinforcement Learning for Interactive Recommendation, , http://dx.doi.org/10.48550/arxiv.2004.08068

Xu W; Zhang X; Yao L; Xue W; Wei B, 2020, A Multi-view CNN-based Acoustic Classification System for Automatic Animal Species Identification, , http://dx.doi.org/10.48550/arxiv.2002.09821

Zhang X; Chen X; Dong M; Liu H; Ge C; Yao L, 2019, Multi-task Generative Adversarial Learning on Geometrical Shape Reconstruction from EEG Brain Signals, , http://dx.doi.org/10.48550/arxiv.1907.13351

Yuan F; Yao L; Benatallah B, 2019, DARec: Deep Domain Adaptation for Cross-Domain Recommendation via Transferring Rating Patterns, , http://dx.doi.org/10.48550/arxiv.1905.10760

Bai L; Yao L; Kanhere SS; Wang X; Sheng QZ, 2019, STG2Seq: Spatial-temporal Graph to Sequence Model for Multi-step Passenger Demand Forecasting, , http://dx.doi.org/10.48550/arxiv.1905.10069

Zhang X; Yao L; Yuan F, 2019, Adversarial Variational Embedding for Robust Semi-supervised Learning, , http://dx.doi.org/10.48550/arxiv.1905.02361

Bai L; Yao L; Kanhere SS; Wang X; Yang Z, 2018, Automatic Device Classification from Network Traffic Streams of Internet of Things, , http://dx.doi.org/10.48550/arxiv.1812.09882

Tran NK; Sheng QZ; Babar MA; Yao L; Zhang WE; Dustdar S, 2018, Internet of Things Search Engine: Concepts, Classification, and Open Issues, , http://dx.doi.org/10.48550/arxiv.1812.02930

Huang C; Yao L; Wang X; Benatallah B; Zhang X, 2018, Software Expert Discovery via Knowledge Domain Embeddings in a Collaborative Network, , http://dx.doi.org/10.48550/arxiv.1810.11305

Zhang X; Yao L; Huang C; Kanhere SS; Zhang D; Zhang Y, 2018, Brain2Object: Printing Your Mind from Brain Signals with Spatial Correlation Embedding, , http://dx.doi.org/10.48550/arxiv.1810.02223

Gao C; He X; Gan D; Chen X; Feng F; Li Y; Chua T-S; Yao L; Song Y; Jin D, 2018, Learning to Recommend with Multiple Cascading Behaviors, , http://dx.doi.org/10.48550/arxiv.1809.08161

Yuan F; Yao L; Benatallah B, 2018, Adversarial Collaborative Auto-encoder for Top-N Recommendation, , http://dx.doi.org/10.48550/arxiv.1808.05361

Huang C; Yao L; Wang X; Benatallah B; Zhang S; Dong M, 2018, Expert Recommendation via Tensor Factorization with Regularizing Hierarchical Topical Relationships, , http://dx.doi.org/10.48550/arxiv.1808.01092

Wang X; Huang C; Yao L; Benatallah B; Dong M, 2018, A Survey on Expert Recommendation in Community Question Answering, , http://dx.doi.org/10.48550/arxiv.1807.05540

Dong M; Yao L; Wang X; Benatallah B; Zhang S, 2018, GrCAN: Gradient Boost Convolutional Autoencoder with Neural Decision Forest, , http://dx.doi.org/10.48550/arxiv.1806.08079

Dong M; Yao L; Wang X; Benatallah B; Huang C; Ning X, 2018, Opinion Fraud Detection via Neural Autoencoder Decision Forest, , http://dx.doi.org/10.48550/arxiv.1805.03379

Zhang X; Yao L; Zhang S; Kanhere SS; Sheng QZ; Liu Y, 2018, Internet of Things Meets Brain-Computer Interface: A Unified Deep Learning Framework for Enabling Human-Thing Cognitive Interactivity, , http://dx.doi.org/10.48550/arxiv.1805.00789

Zhang X; Yao L; Kanhere SS; Liu Y; Gu T; Chen K, 2017, MindID: Person Identification from Brain Waves through Attention-based Recurrent Neural Network, , http://dx.doi.org/10.48550/arxiv.1711.06149

Zhang X; Yao L; Sheng QZ; Kanhere SS; Gu T; Zhang D, 2017, Converting Your Thoughts to Texts: Enabling Brain Typing via Deep Feature Learning of EEG Signals, , http://dx.doi.org/10.48550/arxiv.1709.08820

Zhang X; Yao L; Zhang D; Wang X; Sheng QZ; Gu T, 2017, Multi-Person Brain Activity Recognition via Comprehensive EEG Signal Analysis, , http://dx.doi.org/10.48550/arxiv.1709.09077

Zhang S; Yao L; Sun A; Tay Y, 2017, Deep Learning based Recommender System: A Survey and New Perspectives, , http://dx.doi.org/10.48550/arxiv.1707.07435

Zhang S; Yao L; Xu X, 2017, AutoSVD++: An Efficient Hybrid Collaborative Filtering Model via Contractive Auto-encoders, , http://dx.doi.org/10.48550/arxiv.1704.00551

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