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Spider: Deep Learning-driven Sparse Mobile Traffic Measurement Collection and Reconstruction., , , and . GLOBECOM, page 1-6. IEEE, (2021)Delmu: A Deep Learning Approach to Maximising the Utility of Virtualised Millimetre-Wave Backhauls., , , , and . MLN, volume 11407 of Lecture Notes in Computer Science, page 146-165. Springer, (2018)Field-aware Variational Autoencoders for Billion-scale User Representation Learning., , , , , , , and . ICDE, page 3413-3425. IEEE, (2022)QueryAgent: A Reliable and Efficient Reasoning Framework with Environmental Feedback based Self-Correction., , , , , , and . ACL (1), page 5014-5035. Association for Computational Linguistics, (2024)Microscope: mobile service traffic decomposition for network slicing as a service., , , and . MobiCom, page 38:1-38:14. ACM, (2020)A Machine-Learning-Based Framework for Optimizing the Operation of Future Networks, , , , and . IEEE Commun. Mag., 58 (6): 20--25 (2020)CloudLSTM: A Recurrent Neural Model for Spatiotemporal Point-cloud Stream Forecasting., , , and . AAAI, page 10851-10858. AAAI Press, (2021)AdnFM: An Attentive DenseNet based Factorization Machine for Click-Through-Rate Prediction., , , and . ICCDE, page 1-7. ACM, (2022)QuickSkill: Novice Skill Estimation in Online Multiplayer Games., , , , , , and . CIKM, page 3644-3653. ACM, (2022)Large Language Models can Deliver Accurate and Interpretable Time Series Anomaly Detection., , , , , , , , and . CoRR, (2024)