Journal & Conference Publications

2024

1. J. Bian, L. Wang, K. Yang, C. Shen, J. Xu, "Accelerating Hybrid Federated Learning Convergence under Partial Participation," IEEE Transactions on Signal Processing (accepted), 2024. 

2. J. Bian, J. Xu, "Accelerating Asynchronous Federated Learning Convergence via Opportunistic Mobile Relaying," IEEE Transactions on Vehicular Technology (accepted), 2024.

3. L. Chen, Y. Bai, P. Zhou, Y. Li, Z. Qu, J. Xu, "On Adaptive Edge Microservice Placement: A Reinforcement Learning Approach Endowed with Graph Comprehension," IEEE Transactions on Mobile Computing (accepted), 2024.

4. H. Wang, J. Bian, J. Xu, "On the Local Cache Update Rules in Streaming Federated Learning," IEEE Internet of Things Journal, vol. 11, no. 6, pp. 10808-10816, 2024.

5. L. Zhang, Z. Lu, L. Song, J. Xu, "CrossVision: Real-time On-Camera Video Analysis via Common RoI Load Balancing," IEEE Transactions on Mobile Computing, vol. 23, no. 5, pp. 5027-5039, 2024.

6. J. Xue, Z. Qu, J. Xu, Y. Liu, Z. Lu, "Bandwidth Allocation for Federated Learning with Wireless Providers and Cost Constraints," IEEE Transactions on Mobile Computing vol. 23, no. 6, pp. 7404-7482, 2024.

7. L. Wang, J. Bian, J. Xu, "Adaptive User-Centric Entanglement Routing in Quantum Data Networks," IEEE International Conference on Distributed Computing Systems (ICDCS), 2024.

8. Y. Huang, Q. Liu, J. Xu, "Adversarial Combinatorial Bandits with Switching Cost and Arm Selection Constraints," IEEE International Conference on Computer Communications (INFOCOM), 2024.

9. W. Zhao, X. Li, S. Zhao, J. Xu, Y. Liu, Z. Lu, "Detecting Adversarial Spectrum Attacks via Distance to Decision Boundary Statistics," IEEE International Conference on Computer Communications (INFOCOM), 2024.

10. H. Wang, J. Xu, "Friends to Help: Saving Federated Learning from Client Dropout," IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2024.

11. Y. Peng, J. Bian, J. Xu, "FedMM: Federated Multi-Modal Learning with Modality Heterogeneity in Computational Pathology," IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2024.

12. L. Wang, J. Bian, J. Xu, "Federated Learning with Instance-Dependent Noisy Label," IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2024.

13. J. Bian, L. Wang, S. Ren, J. Xu, "CAFE: Carbon-Aware Federated Learning in Geographically Distributed Data Centers," The 15th ACM International Conference on Future and Sustainable Energy Systems (e-Energy), 2024. (Best Paper Nomination)

2023

1. Y. Bai, L. Chen, J. Xu, "NeuE: Automated Neural Network Ensembles for Edge Intelligence," IEEE Transactions on Emerging Topics in Computing, vol. 11, no. 2, pp.485-496, 2023. 

2. Y. Bai, L. Chen, S. Ren, J. Xu, "Automated Customization of On-Thing Inference for Quality-of-Experience Enhancement," IEEE Transactions on Computers, vol. 72, no. 2, pp. 1329-1342, 2023. 

3. Z. Qu, X. Li, J. Xu, B. Tang, Z. Lu, Y. Liu, "On the Convergence of Multi-Server Federated Learning with Overlapping Area," IEEE Transactions on Mobile Computing, vol. 12, no. 11, pp. 6647-6662, 2023. 

4. Y. Bai, L. Chen, J. Li, J. Wu, P. Zhou, Z. Xu, J. Xu, "Multi-Core Federated Learning for Mobile Edge Computing Platforms," IEEE Internet of Things Journal, vol. 10, no. 7, pp. 5940-5952, 2023. 

5. J. Bian, J. Xu, "Mobility-assisted Federated Learning for Vehicular Edge Computing," The 57th Asilomar Conference on Signals, Systems and Computers, 2023. (Invited Paper). 

6. J. Bian, C. Shen, J. Xu, "Federated Learning via Indirect Server-Client Communications,"  Annual Conference on Information Sciences and Systems (CISS), 2023. (Invited Paper)

7. Y. Huang, L. Zhang, J. Xu, "Adversarial Group Linear Bandits and Its Application to Collaborative Edge Inference," IEEE International Conference on Computer Communications (INFOCOM), 2023.

8. L. Zhang, J. Xu, "E3Pose: Energy-efficient Edge-assisted Multi-camera System for Multi-Human 3D Pose Estimation," ACM/IEEE Conference on Internet of Things Design and Implementation (IoTDI), CPS-IoT Week, 2023. 

9. J. Bian, J. Xu, "Client Clustering in Energy-Efficient Clustered Federated Learning in Wireless Networks," UbiComp/ISWC'23 Workshop on Combining Physical and Data-Driven Knowledge in Ubiquitous Computing, 2023.

2022

1. Z. Qu, R. Duan, L. Chen, J. Xu, Z. Lu, Y. Liu, "Context-Aware Online Client Selection for Hierarchical Federated Learning," IEEE Transactions on Parallel and Distributed Systems, vol. 33, no. 12, 2022.

2. B. Lu, J. Yang, J. Xu, S. Ren, "Improving QoE of Deep Neural Network Inference on Edge Devices: A Bandit Approach," IEEE Internet of Things Journal, vol. 9, no. 21, pp. 21409-21420, 2022.

3. L. Zhang, J. Xu, "Learning the Optimal Partition for Collaborative DNN Training with Privacy Requirements", IEEE Internet of Things Journal, vol. 9, no. 13, pp. 11168-11178, 2022. 

4. Z. Luo, S. Zhao, Z. Lu, J. Xu, Y. Sagduyu, "When Attackers Meet AI: Learning-empowered Attacks in Cooperative Spectrum Sensing," IEEE Transactions on Mobile Computing, vol. 21, no. 5, pp. 1892-1908, 2022. 

5. J. Xu, H. Wang, L. Chen, "Bandwidth Allocation for Multiple Federated Learning Services in Wireless Edge Networks", IEEE Transactions on Wireless Communications, vol. 21, no. 4, pp. 2534-2546, 2022.

6. Y. Bai, L. Chen, M. Abdel-Mottaleb, J. Xu, "Automated Ensemble for Deep Learning Inference on Edge Computing Platforms," IEEE Internet of Things Journal, vol. 9, no. 6, pp. 4202-4213, 2022.

7. C. Shen, J. Yang, J. Xu, "On Federated Learning with Energy Harvesting Clients", IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2022. (Invited Paper).

2021

1. Z. Qu, S. Zhao, J. Xu, Z. Lu, Y. Liu, "How to Test the Randomness from the Wireless Channel for Security?", IEEE Transactions on Information Forensics & Security, vol. 16, pp. 3753-3766, 2021. 

2. L. Chen, J. Xu, "Seek Common While Shelving Differences: Orchestrating Deep Neural Networks for Edge Service Provisioning," IEEE Journal on Selected Areas in Communications - Special issue on "Machine Learning for Communication Networks", vol. 39, no. 1, pp. 251-264, 2021.

3. J. Xu, H. Wang, "Client Selection and Bandwidth Allocation in Wireless Federated Learning Networks: A Long-Term Perspective," IEEE Transactions on Wireless Communications, vol. 20, no. 2, pp. 1188-1200, 2021.

4. L. Chen, C. Shen, P. Zhou, J. Xu, "Collaborative Service Placement for Edge Computing in Dense Small Cell Networks," IEEE Transactions on Mobile Computing, vol. 20, no. 2, pp. 377-390, 2021. 

5. S. Maghsudi, A. Lan, J. Xu, M. van der Schaar, "Personalized Education in the AI Era: What to Expect Next?", IEEE Signal Processing Magazine, vol. 38, no. 3, 2021. 

6. C. Shen, J. Xu, S. Zheng, X. Chen, "Resource Rationing for Wireless Federated Learning: Concepts, Benefits, and Challenges," IEEE Communications Magazine, Data Science and Artificial Intelligence Series, vol. 59, no. 6, 2021. 

7. L. Zhang, L. Chen, J. Xu, "Autodidactic Neurosurgeon: Collaborative Deep Inference for Mobile Edge Intelligence via Online Learning," ACM The Web Conference (WWW), 2021. 

8. Y. Bai, L. Chen, L. Zhang, M. Abdel-Mottaleb, J. Xu, "Adaptive Deep Neural Network Ensemble for Inference-as-a-Service on Edge Computing Platforms," IEEE International Conference on Mobile Ad-Hoc and Smart Systems (MASS), 2021

9. Z. Luo, S. Zhao, R. Duan, Z. Lu, Y. E. Sagduyu, J. Xu, "Low-cost Influence-Limiting Defense against Adversarial Machine Learning Attacks in Cooperative Spectrum Sensing," The ACM Workshop on Wireless Security and Machine Learning (in conjunction with WiSec), 2021. 

2020

1. L. Chen, L. Song, J. Chakareski, J. Xu, "Collaborative Content Placement among Wireless Edge Caching Stations with Time-to-Live Cache," IEEE Transactions on Multimedia, vol. 22, no. 2, pp. 432-444, 2020. 

2. P. Zhou, J. Xu, W. Wang, C. Jiang, K. Wang and J. Hu, "Human-Behavior and QoE-Aware Dynamic Channel Allocation for 5G Networks: A Latent Contextual Bandit Learning Approach," IEEE Transactions on Cognitive Communications and Networking, vol. 6, no. 2, pp. 436-451, 2020. 

3. Y. Yang, J. Xu, Z. Xu, P. Zhou, T. Qiu, "Quantile Context-Aware Social IoT Service Big Data Recommendation with D2D Communication," IEEE Internet of Things Journal, vol. 7, no. 6, pp. 5533-5548, 2020. 

4. Y. Bai, L. Chen, L. Song, J. Xu, "Risk-Aware Edge Computation Offloading using Bayesian Stackelberg Game," IEEE Transactions on Network and Service Management, vol. 17, no. 2, pp. 1000-1012, 2020. 

5. L. Zhang, J. Xu, "Differential Security Game in Heterogeneous Device-to-Device Offloading Network under Epidemic Risks", IEEE Transactions on Network Science and Engineering, vol. 7, no. 3, pp. 1852-1861, 2020.

6. L. Chen, Z. Lu, P. Zhou, J. Xu, "Learning Optimal Sniffer Channel Assignment for Small Cell Cognitive Radio Networks," IEEE International Conference on Computer Communications (INFOCOM), 2020. 

7. Z. Luo, S. Zhao, Z. Lu, Y. Sagduyu, J. Xu, "Adversarial Machine Learning based Partial-Model Attack in IoT," The ACM Workshop on Wireless Security and Machine Learning (in conjunction with WiSec), 2020.

8. L. Zhang, J. Xu, "Fooling Edge Computation Offloading via Stealthy Interference Attack," Workshop on Edge Computing and Communications (EdgeComm) (in conjunction with SEC), 2020.

2019

1. P. Zhou, J. Xu, W. Wang, H. Huang, Y. Hu, D. Wu, S. Ji, "Toward Optimal Adaptive Online Shortest Path Routing with Acceleration under Jamming Attack," IEEE/ACM Transactions on Networking, vol. 27, no. 5, pp. 1815-1829, 2019. 

2. L. Chen, J. Xu, "Budget-constrained Edge Service Provisioning with Demand Estimation via Bandit Learning," IEEE Journal on Selected Areas in Communications - Special issue on "Machine Learning in Wireless Communication", vol. 37, no. 10, pp. 2364-2376, 2019. 

3. J. Chakareski, S. Naqvi, N. Mastronarde, J. Xu, F. Afghah, A. Razi, "An Energy Efficient Framework for UAV-Assisted Millimeter Wave 5G Heterogeneous Cellular Networks," IEEE Transactions on Green Communications and Networking, vol. 3, no. 1, pp. 37-44, 2019. 

4. Y. Feng, P. Zhou, J. Xu, S. Ji, D. O. Wu, "Video Big Data Retrieval Over Media Cloud: A Context-aware Online Learning Approach," IEEE Transactions on Multimedia, vol. 21, no. 7, pp. 1762-1777, 2019.

5. P. Zhou, K. Wang, J. Xu, D. O. Wu, "Differentially-Private and Trustworthy Online Social Multimedia Big Data Retrieval in Edge Computing," IEEE Transactions on Multimedia, vol. 21, no. 3, pp. 539-554, 2019. 

6. Y. Bai, L. Chen, L. Song, J. Xu, “Bayesian Stackelberg Game for Risk-aware Edge Computation Offloading," ACM Workshop on Moving Target Defense (MTD, in conjunction with ACM CCS), 2019.

7. D. Mu, P. Zhou, Q. Li, R. Li, J. Xu, "Privacy-Preserving MEC-enabled Contextual Online Learning via SDN for Service Selection in IoT," IEEE International Conference on Mobile Ad-hoc and Smart Systems (MASS), 2019.

8. C. Shi, L. Chen, C. Shen, L. Song, J. Xu, "Privacy-Aware Edge Computing Based on Adaptive DNN Partitioning", IEEE Global Communications Conference (GLOBECOM), 2019.

9. L. Zhang, L. Song, J. Xu, "Preventing Malware Propagation in D2D Offloading Networks with Strategic Mobile Users," IEEE Global Communications Conference (GLOBECOM), 2019.

10. M. Yang, L. Song, J. Xu, C. Li, G. Tan, "The Tradeoff Between Privacy and Accuracy in Anomaly Detection Using Federated XGBoost," International Workshop on Federated Machine Learning for User Privacy and Data Confidentiality (in conjunction with IJCAI), 2019.

11. L. Chen, J. Xu, "Task Replication for Vehicular Cloud: Contextual Combinatorial Bandit with Delayed Feedback," IEEE International Conference on Computer Communications (INFOCOM), 2019. 

2018

1. L. Chen, J. Xu, S. Ren, P. Zhou, "Spatio-temporal Edge Service Placement: A Bandit Learning Approach," IEEE Transactions on Wireless Communications, vol. 7, no. 12, pp. 8388-8401, 2018. 

2. J. Xu, L. Chen, K. Liu, C. Shen, "Designing Security-Aware Incentives for Computation Offloading via Device-to-Device Communication," IEEE Transactions on Wireless Communications, vol. 17, no. 9, pp. 6053-6066, 2018 

3. L. Chen, S. Zhou, J. Xu, "Computation Peer Offloading for Energy-Constrained Mobile Edge Computing in Small-Cell Networks," IEEE/ACM Transactions on Networking, vol. 26, no. 4, pp. 1619-1632, 2018. 

4. L. Chen, P. Zhou, L. Gao, J. Xu, "Adaptive Fog Configuration for the Industrial Internet of Things," IEEE Transactions on Industrial Informatics - Special section on "Fog Computing for Industrial Applications", vol. 14, no. 10, pp. 4656-4664, 2018. 

5. L. Chen, J. Xu, Z. Lu, "Contextual Combinatorial Multi-armed Bandits with Volatile Arms and Submodular Reward," Annual Conference on Neural Information Processing Systems (NeurIPS, formerly NIPS), 2018. 

6. L. Song, J. Xu, "Dynamic Edge Caching with Popularity Drifting," IEEE Information Theory Workshop (ITW), 2018. 

7. Z. Liu, L. Jiang, T. Liu, G. Quan, Y. Wang, W. Wen, J. Xu, "DeepN-JPEG: A Deep Neural Network Favorable JPEG-based Image Compression Framework," ACM/IEEE Design Automation Conference (DAC), 2018. 

8. J. Xu, L. Chen, P. Zhou, "Joint Service Caching and Task Offloading for Mobile Edge Computing in Dense Networks," IEEE International Conference on Computer Communications (INFOCOM), 2018. (Most Popular Paper of INFOCOM, June 2019)

9. Y. Hou, P. Zhou, J. Xu, D. Wu, "Course Recommendation of MOOC with Big Data Support: A Contextual Online Learning Approach," IEEE INFOCOM Workshop on Knowledge Centric Networking (KCN), 2018. 

10. H. Wu, L. Chen, C. Shen, W. Wen, J. Xu, "Online Geographical Load Balancing for Energy-Harvesting Mobile Edge Computing," IEEE International Conference on Communications (ICC), 2018. 

11. S. Naqvi, J. Chakareski, N. Mastronarde, J. Xu, F. Afghah, A. Razi, "Energy Efficiency Analysis of UAV-Assisted mmWave HetNets," IEEE International Conference on Communications (ICC), 2018.

2017

1. Y. Sun, S. Zhou, J. Xu, "EMM: Energy-Aware Mobility Management for Mobile Edge Computing in Ultra Dense Networks", IEEE J. Sel. Areas Commun. - Special issue on "Emerging Technologies in Software-Driven Communication", vol. 35, no. 11, pp. 2637-2646, 2017. 

2. J. Xu, L. Chen, S. Ren, "Online Learning for Offloading and Autoscaling in Energy Harvesting Mobile Edge Computing," IEEE Trans. Cognitive Communications and Networking, vol. 3, no. 3, pp. 361-373, 2017. 

3. J. Xu, K.-H. Moon and M. van der Schaar, "A Machine Learning Approach for Tracking and Predicting Student Performance in Degree Programs," IEEE J. Sel. Topics Signal Process. - Special issue on "Signal Processing and Machine Learning for Education and Human Learning at Scale", vol. 11, no. 5, pp. 742-753, 2017. 

4. L. Chen, J. Xu, S. Zhou, "Computation Peer Offloading in Mobile Edge Computing with Energy Budgets," IEEE Global Communications Conference (GLOBECOM), 2017.

5. A. Zhou, Y. Feng, P. Zhou, J. Xu, "Social Intimacy Based IoT Services Mining of Massive Data," IEEE International Conference on Data Mining (ICDM) Workshop on Data Mining for Services, 2017.

6. L. Chen, J. Xu, "Socially Trusted Collaborative Edge Computing in Ultra Dense Networks," IEEE/ACM Symposium on Edge Computing (SEC), 2017. (arXiv: 1705.03501)

7. J. Xu, Y. Sun, L. Chen, S. Zhou, "E2M2: Energy Efficient Mobility Management in Dense Small Cells with Mobile Edge Computing," IEEE International Conference on Communications (ICC), 2017

8. L. Chen, S. Zhou, J. Xu, "Energy Efficient Mobile Edge Computing in Dense Cellular Networks," IEEE International Conference on Communications (ICC), 2017.

9. J. Xu, Y. Han, D. Marcu, M. van der Schaar, "Progressive Prediction of Student Performance in College Programs," AAAI Conference on Artificial Intelligence (AAAI), 2017.

2016

1. S. Li, J. Xu, M. van der Schaar and W. Li, "Trend-Aware Video Caching through Online Learning," IEEE Trans. Multimedia, vol. 18, no. 12, pp. 2503-2516, 2016.

2. J. Xu, T. Xing and M. van der Schaar, "Personalized Course Sequence Recommendation," IEEE Trans. Signal Process., vol. 64, no. 20, pp. 5340-5352, 2016.

3. J. Xu, L. Song, J. Y. Xu, G. Pottie and M. van der Schaar, "Personalized Active Learning for Activity Classification using Wireless Wearable Sensors," IEEE J. Sel. Topics Signal Process., vol. 10, no. 5, pp. 865-876, 2016.

4. Z. Yuan, J. Xu, Y. Xue and M. van der Schaar, "Bits Learning: User-adjustable Privacy versus Accuracy in Internet Traffic Classification",  IEEE Communications Letters, vol. 20, no. 4, pp. 704-707, 2016.

5. Y. Meier, J. Xu, O. Atan, M. van der Schaar, "Predicting Grades," IEEE Trans. Signal Process., vol. 64, no. 4, pp. 959-972, 2016. 

6. N. Mastronarde, V. Patel, J. Xu, M. van der Schaar, and L. Liu, "To Relay or Not to Relay: Learning Device-to-Device Relaying Strategies in Cellular Networks,"  IEEE Trans. Mobile Computing, vol. 15, no. 6, pp. 1569-1585, 2016. 

7. L. Song, W. Hsu, J. Xu and M. van der Schaar, "Using Contextual Learning to Improve Diagnostic Accuracy: Application in Breast Cancer Screening," IEEE Journal of Biomedical and Health Informatics, vol. 20, no. 3, pp. 902-914, May. 2016.

8. S. Li, J. Xu, M. van der Schaar, and W. Li, "Popularity-Driven Content Caching," IEEE International Conference on Computer Communications (INFOCOM), 2016.

9. J. Xu, Q. Cai, C. Shen, "DARC: Timely Classification with Randomly Delayed Features," IEEE Global Communications Conference (GLOBECOM), 2016.

10. J. Xu, S. Ren, "Online Learning for Offloading and Autoscaling in Renewable-Powered Mobile Edge Computing," IEEE Global Communications Conference (GLOBECOM), 2016.

11. J. Xu, T. Xing, M. van der Schaar, "Personalized Course Sequence Recommendation," ICML Workshop on Machine Learning for Digital Education and Assessment Systems, 2016. 

12. J. Xu, "Relaxation for Constrained Decentralized Markov Decision Processes," International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2016.

2015 and earlier

1. J. Xu and M. van der Schaar, "Incentive-Compatible Demand-Side Management for Smart Grids based on Review Strategies," EURASIP Journal on Advances in Signal Processing, vol. 51, Jun. 2015.

2. M. Wolf, M. van der Schaar, H. Kim and J. Xu, "Caring Analytics for Adults with Special Needs," IEEE Design & Test - Special issue on "Cyber-Physical systems for Medical Applications", vol. 32, no. 5, pp. 35-44, Oct. 2015.

3. C. Shen, J. Xu and M. van der Schaar, "Silence is Gold: Strategic Interference Mitigation Using Tokens in Heterogeneous Small Cell Networks," IEEE J. Sel. Areas Commun. - Special issue on "Heterogenous Communication Networks", vol. 33, no. 6, pp. 1097-1111, March. 2015.

4. J. Xu, D. Deng, U. Demiryurek, C. Shahabi and M. van der Schaar, "Mining the Situation: Spatiotemporal Traffic Prediction with Big Data," IEEE J. Sel. Topics Signal Process. - Special issue on "Signal Processing for Big Data", vol. 9, no. 4, pp. 716-727, Jun. 2015. (JSTSP Popular Article)

5. J. Xu, C. Tekin and M. van der Schaar, "Distributed Multi-Agent Online Learning Based on Global Feedback," IEEE Trans. Signal Process., vol. 63, no. 9, pp. 2225-2238, May. 2015.

6. J. Xu and M. van der Schaar, "Efficient Working and Shirking in Information Sharing Networks," IEEE J. Sel. Areas Commun. - Bonus Issue for Emerging Technologies, vol. 33, no. 4, pp. 651-662, Jan. 2015.

7. J. Xu, M. van der Schaar, J. Liu and H. Li, "Forecasting Popularity of Videos using Social Media," IEEE J. Sel. Topics Signal Process. - Special issue on "Situational Awareness from Networked Sensors and Social Media", vol. 9, no. 2, pp. 330-343, Nov. 2014. 

8. J. Xu, Y. Song, and M. van der Schaar, "Sharing in Networks of Strategic Agents," IEEE J. Sel. Topics Signal Process. - Special issue on "Signal Processing for Social Networks", vol. 8, no. 4, pp. 717-731, Apr. 2014.

9. J. Xu, Y. Andreopoulos, Y. Xiao and M. van der Schaar, "Non-stationary Resource Allocation Policies for Delay-constrained Video Streaming: Application to Video over Internet-of-Things-enabled Networks," IEEE J. Sel. Areas Commun. - Special issue on "Adaptive Media Streaming", vol. 32, no. 4, pp. 782-794, Apr. 2014.

10. J. Xu (with M. van der Schaar and W. Zame), "Efficient Online Exchange via Fiat Money,'' Economic Theory, vol. 54, no. 2, pp. 211-248, Oct. 2013.

11. J. Xu and M. van der Schaar, "Token System Design for Autonomic Wireless Relay Networks," IEEE Trans. Commun., vol. 61, no. 7, pp. 2924-2935, 2013.

12. W. Zame, J. Xu and M. van der Schaar, "Cooperative Multi-Agent Learning and Coordination for Cognitive Radio Networks," IEEE J. Sel. Areas Commun. - Special issue on "Cognitive Radio Series", vol. 32, no. 3, pp. 464-477, Dec. 2013.

13. W. Zame, J. Xu and M. van der Schaar, "Winning the Lottery: Learning Perfect Coordination with Minimal Feedback," IEEE J. Sel. Topics Signal Process. - Special issue on "Learning-Based Decision Making in Dynamic Systems under Uncertainty", vol. 7, no. 5, pp. 846-857, April 2013.

14. S. Zhou, J. Xu and Z. Niu, "Interference-Aware Relay Selection Scheme for Two-Hop Relay Networks with Multiple Source-Destination Pairs," IEEE Trans. Vehi. Tech., vol. 62, no. 5, pp. 2327-2338, Jan. 2013.

15. J. Xu and M. van der Schaar, "Social Norm Design for Information Exchange Systems with Limited Observations," IEEE J. Sel. Areas Commun. - Special issue on "Economics of Communication Networks and Systems", vol. 30, no. 11, pp. 2126-2135, Dec. 2012.

16. Y. Meier, J. Xu, O. Atan, and M. van der Schaar, "Personalized Grade Prediction: A Data Mining Approach," IEEE International Conference on Data Mining (ICDM), 2015.

17. J. Xu, M. van der Schaar, J. Liu and H. Li, "Timely Popularity Forecasting based on Social Networks," IEEE International Conference on Computer Communications (INFOCOM), 2015.

18. J. Xu, D. Sow, D. Turaga and M. van der Schaar, "Online Transfer Learning for Differential Diagnosis Determination," AAAI Workshop on the World Wide Web and Public Health Intelligence, 2015.

19. J. Xu, D. Deng, U. Demiryurek, C. Shahabi and M. van der Schaar, "Context-Aware Online Spatiotemporal Traffic Prediction,'' ICDM Workshop on Spatial and Spatio-Temporal Data Mining, 2015.

20. J. Xu, S. Zhang and M. van der Schaar, "Network Evolution with Incomplete Information and Learning," Allerton Conference on Communication, Control and Computing, 2014.

21. J. Xu, J. Y. Xu, L. Song, G. Pottie, and M. van der Schaar, "Context-Driven Online Learning for Activity Classification in Wireless Health," IEEE Global Communications Conference (GLOBECOM),  2014.

22. C. Shen, J. Xu, and M. van der Schaar, "Silence is Gold: Strategic Small Cell Interference Management Using Tokens," IEEE Global Communications Conference (GLOBECOM), 2014.

23. J. Xu, Y. Song, and M. van der Schaar, "Incentivizing Information Sharing in Networks," IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2014.

24. J. Xu, Y. Zhang and M. van der Schaar, "Rating Systems for Enhanced Cyber-Security Investments," in IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2013.

25. J. Xu, C. Tekin and M. van der Schaar, "Learning Optimal Classifier Chains for Real-time Big Data Mining," Allerton Conference on Communication, Control and Computing, 2013.

26. N. Mastronarde, V. Patel, J. Xu, and M. van der Schaar, "Learning Relaying Strategies in Cellular D2D Networks with Token-Based Incentives," Globecom 2013 Workshop - Emerging Technologies for LTE-Advanced and Beyond-4G.

27. W. Zame, J. Xu, and M. van der Schaar, "Learning Perfect Coordination with Minimal Feedback in Wireless Multi-Access Communications," in in IEEE Global Communications Conference (GLOBECOM),  2013.

28. J. Xu and M. van der Schaar, "Incentive Design for Heterogeneous User-Generated Content Networks," SIGMETRICS Workshop on Pricing and Incentives in Networks and Systems (W-PIN + Netecon), 2013.

29. S. Won and I. Cho and K. Sudusinghe and J. Xu and Y. Zhang, M. van der Schaar and S. S. Bhattacharyya, "A Design Methodology for Distributed Adaptive Stream Mining Systems," International Conference on Computational Science, 2013.

30. J. Xu and M. van der Schaar, "Sustaining Cooperation in Social Exchange Networks with Incomplete Global Information," in IEEE Conference on Decision and Control (CDC) 2012.

31. J. Xu, W. Zame and M. van der Schaar, "Token Economy for Online Exchange Systems," International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2012.

32. J. Xu, W. Zame and M. van der Schaar, "Token-based Incentive Protocol Design for Online Exchange Systems," International Conference on Game Theory for Networks (GameNets), 2012.

33. J. Xu, M. van der Schaar, "Designing Incentives for Wireless Relay Networks using Tokens," International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt), 2012.

34. J. Xu, Y. Wu, Z. Niu, "Exploiting Multiuser Diversity in OFDMA Wireless Mesh Networks by Fractional Spatial Reuse," IEEE International Conference on Communications (ICC), 2010.

35. J. Xu, S. Zhou, Z. Niu, "Interference-Aware Relay Selection for Multiple Source-Destination Cooperative Networks", Asia-Pacific Conference on Communications (APCC), 2009. (Best Paper Award)

Book Chapter

1. M. van der Schaar, J. Xu, S. Zhang, C. Tekin, "Marketing and advertising, trend prediction, recommendation systems, and crowdsourcing", Cooperative and Graph Signal Processing: Principles and Applications, Eds. P. Djuric and C. Richard, Elsevier, 2018.

2. J. Xu, L. Chen, "Security-aware incentives design for mobile device-to-device offloading," Proactive and Dynamic Network Defense, Eds. C. Wang and Z. Lu, Springer, 2019. 

3. J. Xu, K. Sudusinghe, M. van der Schaar, S. Bhattacharyya, "Adaptive Data Stream Mining (DSM) Systems," Handbook of Dynamic Data Driven Application Systems, vol. 2, pp. 705-722, Springer, 2023.