Select Publications
Preprints
, 2023, Guided Image-to-Image Translation by Discriminator-Generator Communication, http://dx.doi.org/10.48550/arxiv.2303.03598
, 2022, A Bibliometric Analysis and Review on Reinforcement Learning for Transportation Applications, http://dx.doi.org/10.48550/arxiv.2210.14524
, 2022, Intrinsically Motivated Reinforcement Learning based Recommendation with Counterfactual Data Augmentation, http://dx.doi.org/10.48550/arxiv.2209.08228
, 2022, Plug-and-Play Model-Agnostic Counterfactual Policy Synthesis for Deep Reinforcement Learning based Recommendation, http://dx.doi.org/10.48550/arxiv.2208.05142
, 2022, A Survey on Participant Selection for Federated Learning in Mobile Networks, http://dx.doi.org/10.48550/arxiv.2207.03681
, 2022, Unsupervised Knowledge Adaptation for Passenger Demand Forecasting, http://dx.doi.org/10.48550/arxiv.2206.04053
, 2022, Disentangled and Side-aware Unsupervised Domain Adaptation for Cross-dataset Subjective Tinnitus Diagnosis, http://dx.doi.org/10.48550/arxiv.2205.03230
, 2022, Side-aware Meta-Learning for Cross-Dataset Listener Diagnosis with Subjective Tinnitus, http://dx.doi.org/10.48550/arxiv.2205.03231
, 2021, Adversarial Robustness of Deep Reinforcement Learning based Dynamic Recommender Systems, http://dx.doi.org/10.48550/arxiv.2112.00973
, 2021, Rethink, Revisit, Revise: A Spiral Reinforced Self-Revised Network for Zero-Shot Learning, http://arxiv.org/abs/2112.00410v1
, 2021, Locality-Sensitive Experience Replay for Online Recommendation, http://dx.doi.org/10.48550/arxiv.2110.10850
, 2021, Generative Adversarial Reward Learning for Generalized Behavior Tendency Inference, http://dx.doi.org/10.48550/arxiv.2105.00822
, 2021, An Internet of Things Service Roadmap, http://dx.doi.org/10.48550/arxiv.2103.03043
, 2020, Knowledge Adaption for Demand Prediction based on Multi-task Memory Neural Network, http://dx.doi.org/10.48550/arxiv.2009.05777
, 2020, Recommender Systems for the Internet of Things: A Survey, http://arxiv.org/abs/2007.06758v1
, 2020, Spectrum-Guided Adversarial Disparity Learning, http://dx.doi.org/10.1145/3394486.3403054
, 2020, Momentum Contrastive Learning for Few-Shot COVID-19 Diagnosis from Chest CT Images, http://dx.doi.org/10.48550/arxiv.2006.13276
, 2020, NP-PROV: Neural Processes with Position-Relevant-Only Variances, http://dx.doi.org/10.48550/arxiv.2007.00767
, 2020, Adversarial Attacks and Detection on Reinforcement Learning-Based Interactive Recommender Systems, http://dx.doi.org/10.48550/arxiv.2006.07934
, 2020, Agglomerative Neural Networks for Multi-view Clustering, http://arxiv.org/abs/2005.05556v1
, 2020, Deep Conversational Recommender Systems: A New Frontier for Goal-Oriented Dialogue Systems, http://dx.doi.org/10.48550/arxiv.2004.13245
, 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
, 2020, Knowledge-guided Deep Reinforcement Learning for Interactive Recommendation, http://dx.doi.org/10.48550/arxiv.2004.08068
, 2020, A Multi-view CNN-based Acoustic Classification System for Automatic Animal Species Identification, http://dx.doi.org/10.48550/arxiv.2002.09821
, 2019, Multi-task Generative Adversarial Learning on Geometrical Shape Reconstruction from EEG Brain Signals, http://dx.doi.org/10.48550/arxiv.1907.13351
, 2019, DARec: Deep Domain Adaptation for Cross-Domain Recommendation via Transferring Rating Patterns, http://dx.doi.org/10.48550/arxiv.1905.10760
, 2019, STG2Seq: Spatial-temporal Graph to Sequence Model for Multi-step Passenger Demand Forecasting, http://dx.doi.org/10.48550/arxiv.1905.10069
, 2019, Adversarial Variational Embedding for Robust Semi-supervised Learning, http://dx.doi.org/10.48550/arxiv.1905.02361
, 2018, Automatic Device Classification from Network Traffic Streams of Internet of Things, http://dx.doi.org/10.48550/arxiv.1812.09882
, 2018, Internet of Things Search Engine: Concepts, Classification, and Open Issues, http://dx.doi.org/10.48550/arxiv.1812.02930
, 2018, Software Expert Discovery via Knowledge Domain Embeddings in a Collaborative Network, http://dx.doi.org/10.1016/j.patrec.2018.10.030
, 2018, Brain2Object: Printing Your Mind from Brain Signals with Spatial Correlation Embedding, http://dx.doi.org/10.48550/arxiv.1810.02223
, 2018, Learning to Recommend with Multiple Cascading Behaviors, http://dx.doi.org/10.48550/arxiv.1809.08161
, 2018, Adversarial Collaborative Auto-encoder for Top-N Recommendation, http://dx.doi.org/10.48550/arxiv.1808.05361
, 2018, Expert Recommendation via Tensor Factorization with Regularizing Hierarchical Topical Relationships, http://arxiv.org/abs/1808.01092v2
, 2018, A Survey on Expert Recommendation in Community Question Answering, http://arxiv.org/abs/1807.05540v1
, 2018, GrCAN: Gradient Boost Convolutional Autoencoder with Neural Decision Forest, http://dx.doi.org/10.48550/arxiv.1806.08079
, 2018, Opinion Fraud Detection via Neural Autoencoder Decision Forest, http://dx.doi.org/10.48550/arxiv.1805.03379
, 2018, NeuRec: On Nonlinear Transformation for Personalized Ranking, http://arxiv.org/abs/1805.03002v3
, 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
, 2017, MindID: Person Identification from Brain Waves through Attention-based Recurrent Neural Network, http://dx.doi.org/10.48550/arxiv.1711.06149
, 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
, 2017, Multi-Person Brain Activity Recognition via Comprehensive EEG Signal Analysis, http://dx.doi.org/10.48550/arxiv.1709.09077
, 2017, Deep Learning based Recommender System: A Survey and New Perspectives, http://dx.doi.org/10.48550/arxiv.1707.07435
, 2017, AutoSVD++: An Efficient Hybrid Collaborative Filtering Model via Contractive Auto-encoders, http://dx.doi.org/10.48550/arxiv.1704.00551
, 2017, Intent Recognition in Smart Living Through Deep Recurrent Neural Networks, http://dx.doi.org/10.48550/arxiv.1702.06830
, 2016, Searching for the Internet of Things on the Web: Where It Is and What It Looks Like, http://dx.doi.org/10.48550/arxiv.1607.06884
, 2016, Uncovering Locally Discriminative Structure for Feature Analysis, http://dx.doi.org/10.48550/arxiv.1607.02559
, 2015, Unveiling Contextual Similarity of Things via Mining Human-Thing Interactions in the Internet of Things, http://dx.doi.org/10.48550/arxiv.1512.08493
, 2015, Up in the Air: When Homes Meet the Web of Things, http://dx.doi.org/10.48550/arxiv.1512.06257