Jia (Kevin) Liu,

Associate Professor of Electrical and Computer Engineering, The Ohio State University

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Publications
[Google Scholar] [DBLP] [ResearchGate]
（Underlined are students or postdocs that I supervise, '∗' marks co-primary authors）
Note: Materials on this web site are subject to the copyright of the authors and the corresponding publishers, e.g., IEEE and ACM, and are provided for personal and academic use only. All publications on this web page are intended for quick dissemination of new findings and research results.

Journals

  1. Xiaowen Chu, Shadi Ibrahim, Jia Liu, Shiqiang Wang, Chuan Wu, and Rongfei Zeng, "Interplay between Machine Learning and Networking Systems,'' IEEE Network, vol. 37, no. 4, pp. 72-73, Jul.-Aug. 2023.

  2. Xin Zhang, Jia Liu, and Zhengyuan Zhu, "Learning Coefficient Heterogeneity over Networks: A Distributed Spanning-Tree-Based Fused-Lasso Regression,'' Journal of the American Statistical Association, accepted in Sept. 2022, to appear.

  3. Menglu Yu, Jia Liu, Chuan Wu, Bo Ji, and Elizabeth S. Bentley, "Toward Efficient Online Scheduling for Distributed Machine Learning Systems,'' IEEE Transactions on Network Science and Engineering (TNSE), vol. 9, no. 4, pp. 1951-1969, Jul.-Aug. 2022.

  4. Hongsen Shi*, Jia Liu*, and Qian Chen, "An RC-Network Approach for HVAC Precooling Optimization in Buildings,'' IEEE Transactions on Sustainable Computing, vol. 7, no. 3, pp. 512-526, Jul.-Sep. 2022 (*Co-primary authors, corresponding authors).

  5. Kuangyu Zheng, Xiaorui Wang, and Jia Liu, "Distributed Traffic Flow Consolidation for Power Efficiency of Large-scale Data Center Network,'' IEEE Transactions on Cloud Computing (TCC), vol. 10, no. 2, pp. 996-1007, Apr.-Jun. 2022

  6. Bin Li* and Jia Liu*, "Achieving Information Freshness with Selfish and Rational Users in Mobile Crowd-Learning,'' IEEE Journal on Selected Areas in Communications (JSAC), vol. 39, no. 5, pp. 1266-1276, May 2021 (*Co-primary authors).

  7. Bin Li, Jia Liu, and Bo Ji, "Low-Overhead Wireless Uplink Scheduling for Large-Scale Internet-of-Things,'' IEEE Transactions on Mobile Computing (TMC), vol. 20, no. 2, pp. 577-587, Feb. 2021.

  8. Fengjiao Li, Jia Liu, and Bo Ji, "Combinatorial Sleeping Bandits with Fairness Constraints,'' IEEE Transactions on Network Science and Engineering (TNSE), vol. 7, no. 3, pp. 1799-1813, Jul. 2020.

  9. Jia Liu and Elizabeth S. Bentley, "Hybrid-Beamforming-Based Millimeter-Wave Cellular Network Optimization,'' IEEE Journal on Selected Areas in Communications (JSAC), vol. 37, no. 12, pp. 2799-2813, Dec. 2019.

  10. Jia Liu, Atilla Eryilmaz, Ness B. Shroff, and Elizabeth S. Bentley, "Understanding the Impacts of Limited Channel State Information on Massive MIMO Cellular Network Optimization,'' IEEE Journal of Selected Areas in Communications (JSAC), vol. 35, no. 8, pp. 1715-1727, Aug. 2017.

  11. Jia Liu, Ness B. Shroff, Cathy H. Xia, Hanif D. Sherali, "Joint Congestion Control and Routing Optimization: An Efficient Second-Order Distributed Approach,'' IEEE/ACM Transactions on Networking, vol. 24, no. 3, pp. 1404-1420, Jun. 2016.

  12. Yi Shi, Jia Liu, Canming Jiang, Cunhao Gao, and Y. Thomas Hou, "A DoF-Based Link Layer Model for Multi-Hop MIMO Networks,'' IEEE Transactions on Mobile Computing, vol. 13, no. 7, pp. 1395-1408, Jul. 2014.

  13. Jia Liu, Tianyou Kou, Qian Chen, and Hanif D. Sherali, "On Wireless Network Infrastructure Optimization for Cyber-Physical Systems in Future Smart Buildings,'' International Journal on Sensor Networks, special issue on Internet of Things (IoT), vol. 18, no. 3-4, pp. 148-160, 2015.

  14. Jia Liu, Cathy H. Xia, Ness B. Shroff, Xiaodong Zhang, "On Distributed Computation Rate Optimization for Deploying Cloud Computing Programming Frameworks,'' ACM SIGMETRICS Performance Evaluation Review (PER), vol. 40, no. 4, pp. 63-72, Mar. 2013.

  15. Yi Shi, Y. Thomas Hou, Jia Liu, and Sastry Kompella, "Bridging the Gap between Protocol and Physical Models for Wireless Networks,'' IEEE Transactions on Mobile Computing, vol. 12, no. 7, pp. 1404-1416, Jul. 2013.

  16. Jia Liu, Ness B. Shroff, and Hanif D. Sherali, "On Optimal Power Allocation for MIMO Cooperative Networks with Multiple Relays," IEEE Journal on Selected Areas in Communications (JSAC), vol. 30, no. 2, pp. 331-340, Feb. 2012.

  17. Jia Liu, Tianyou Kou, Qian Chen, and H. D. Sherali, "Femtocell Base Station Placement in Commercial Buildings: A Global Optimization Approach," IEEE Journal on Selected Areas in Communications (JSAC), vol. 30, no. 3, pp. 652-663, Apr. 2012.

  18. Sushant Sharma, Yi Shi, Jia Liu, Y. Thomas Hou, and Sastry Kompella, "Network Coding in Cooperative Communications: Friend or Foe?" IEEE Transaction on Mobile Computing, vol. 11, no. 7, pp. 1073-1085, Jul. 2012.

  19. Hui Li, Lingying Zhao, Peter Ling, and Jia Liu, "A Model for Predicting Wireless Signal Transmission Performance of ZigBee-Based Sensor Networks in Residential Houses,'' Transactions of ASHRAE, vol. 118, no. 1, pp. 994-1007, Jan. 2012.

  20. Jia Liu, Y. Thomas Hou, Y. shi, and H. D. Sherali, "Cross-Layer Optimization on Routing and Power Control of MIMO Ad Hoc Networks: Routing, Power Allocation, and Bandwidth Allocation," IEEE Journal on Selected Areas of Communications (JSAC), vol. 26, no.6, pp. 913-926, Aug. 2008.

  21. Jia Liu, Y. Thomas Hou, Y. Shi, and H. D. Sherali, "On the Capacity of Multiuser MIMO Networks with Interference," IEEE Transaction on Wireless Communications, vol. 7, no. 2, pp. 488-494, Feb. 2008.

  22. Jia Liu, Qian Chen, and H. D. Sherali, "Algorithm Design for In-door Wireless Network Infrastructure," submitted to IEEE Transaction on Mobile Computing.

  23. Jia Liu, Ness B. Shroff, Cathy H. Xia, and H. D. Sherali, "Second-Order Distributed Cross-Layer Optimization, Part I: Wireline Networks," submitted to IEEE Transaction on Networking.

  24. Jia Liu, Ness B. Shroff, Cathy H. Xia, and H. D. Sherali, "Second-Order Distributed Cross-Layer Optimization, Part II: Wireless Networks," submitted to IEEE Transaction on Networking.

  25. Jia Liu, Y. Thomas Hou, and Hanif D. Sherali, "Distributed Optimal Load Shedding for Disaster Recovery in Smart Electric Power Grids," submitted to IEEE Transaction on Smart Grid.

Conferences

  1. Zhuqing Liu, Chaosheng Dong, Michinari Momma, Simone Shao, Shaoyuan Xu, Yan Gao, Haibo Yang, and Jia Liu, "STIMULUS: Achieving Fast Convergence and Low Sample Complexity in Stochastic Multi-Objective Learning," in Proc. UAI, Rio de Janeiro, Brazil, Jul. 2025 (acceptance rate: 30.7%).

  2. Jin Shang, Simone Shao, Tian Tong, Fan Yang, Yetian Chen, Yang Jiao, Jia Liu, and Yan Gao, "Divide and Orthogonalize: Efficient Continual Learning with Local Model Space Projection," in Proc. UAI, Rio de Janeiro, Brazil, Jul. 2025 (acceptance rate: 30.7%).

  3. Zhiyao Zhang, Myeung Suk Oh, FNU Hairi, Ziyue Luo, Alvaro Velasquez, and Jia Liu, "Finite-Time Global Optimality Convergence in Deep Neural Actor-Critic Methods for Decentralized Multi-Agent Reinforcement Learning," in Proc. ICML, Vancouver, Canada, Jul. 2025 (acceptance rate: 26.9%).

  4. Srijith Nair, Michael Lin, Peizhong Ju, Amirreza Talebi, Elizabeth Serena Bentley, and Jia Liu, "FSL-SAGE: Accelerating Federated Split Learning via Smashed Activation Gradient Estimation," in Proc. ICML, Vancouver, Canada, Jul. 2025 (acceptance rate: 26.9%).

  5. Ismail Alkhouri*, Cedric Le Denmat*, Yingjie Li, Cunxi Yu, Jia Liu, Rongrong Wang, and Alvaro Velasquez, "Quadratic Differentiable Optimization for the Maximum Independent Set Problem," in Proc. ICML, Vancouver, Canada, Jul. 2025 (*Co-primary authors, acceptance rate: 26.9%).

  6. Zhen Qin, Zhuqing Liu, Songtao Lu, Yingbin Liang, and Jia Liu, "DUET: Decentralized Bilevel Optimization without Lower-Level Strong Convexity," in Proc. ICLR, Singapore, Apr. 2025 (acceptance rate: 32%).

  7. Minghong Fang, Zhuqing Liu, Xuecen Zhao and Jia Liu, "Byzantine-Robust Federated Learning over Ring-All-Reduce Distributed Computing," in Proc. ACM TheWebConf (WWW), Sydney, Australia, Apr. 2025.

  8. Mingjing Xu, Peizhong Ju, Jia Liu, and Haibo Yang, "PSMGD: Periodic Stochastic Multi-Gradient Descent for Fast Multi-Objective Optimization," in Proc. AAAI, Philadelphia, PA, Feb. 2025 (acceptance rate: 23.4%).

  9. Ziyue Luo, Jia Liu, Myungjin Lee, and Ness Shroff, "Prediction-Assisted Online Distributed Deep Learning Workload Scheduling in GPU Clusters," in Proc. IEEE INFOCOM, London, UK, May 2025 (acceptance rate: 18.6%).

  10. Hairi FNU*, Minghong Fang*, Zifan Zhang, Alvaro Velasquez, and Jia Liu, "On the Hardness of Decentralized Multi-Agent Policy Evaluation under Byzantine Attacks," in Proc. IEEE/IFIP WiOpt, Seoul, South Korea, Oct. 2024 (*Co-primary authors, Invited Paper).

  11. Jin Shang, Yang Jiao, Chenghuan Guo, Minghao Sun, Yan Gao, Jia Liu, Michinari Momma, Itetsu Taru, and Yi Sun, "Transitivity-Encoded Graph Attention Networks for Complementary Item Recommendation," in Proc. IEEE ICDM, Abu Dhabi, UAE, Dec. 2024 (acceptance rate: 10.9%).

  12. Peizhong Ju, Haibo Yang, Jia Liu, Yingbin Liang, and Ness B. Shroff, "Can We Theoretically Quantify the Impacts of Local Updates on the Generalization Performance of Federated Learning?," in Proc. ACM MobiHoc, Athens, Greece, Oct. 2024 (acceptance rate: 24.5%).

  13. Minghe Zhang, Chaosheng Dong, Jinmiao Fu, Tianchen Zhou, Jia Liang, Jia Liu, Bo Liu, Michinari Momma, Bryan Wang, Yan Gao, and Yi Sun, "AdaSelection: Accelerating Deep Learning Training through Data Subsampling?," in Proc. SIGKDD Workshop on Resource-Efficient Learning for Knowledge Discovery, Barcelona, Spain, Jul. 2024.

  14. Haibo Yang, Peiwen Qiu, Prashant Khanduri, Minghong Fang, and Jia Liu, "Understanding Server-Assisted Federated Learning in the Presence of Incomplete Client Participation," in Proc. ICML, Vienna, Austria, Jul. 2024 (acceptance rate: 27.5%).

  15. Tianchen Zhou*, FNU Hairi*, Haibo Yang, Jia Liu, Tian Tong, Fan Yang, Michinari Momma, Yan Gao, "Finite-Time Convergence and Sample Complexity of Actor-Critic Multi-Objective Reinforcement Learning," in Proc. ICML, Vienna, Austria, Jul. 2024 (acceptance rate: 27.5%).

  16. Minghong Fang, Zifan Zhang, Hairi FNU, Prashant Khanduri, Jia Liu, Songtao Lu, Neil Gong, Yuchen Liu, "Toward Byzantine-Robust Decentralized Federated Learning," in Proc. ACM CCS, Salt Lake City, UT, Oct. 2024 (acceptance rate: 19%).

  17. Yanhui Guo, Shaoyuan Xu, Jinmiao Fu, Jia Liu, Chaosheng Dong, and Bryan Wang, "Q-Tuning: Queue-based Prompt Tuning for Lifelong Few-shot Language Learning," in Proc. NAACL, Mexico City, Mexico, June 2024.

  18. Yang Jiao, Fan Yang, Yetian Chen, Yan Gao, Jia Liu, and Yi Sun, "Rethinking Sequential Relationships: Improving Sequential Recommenders with Inter-Sequence Data Augmentation," in Proc. ACM TheWebConf (WWW), Singapore, May 2024 (acceptance rate: 20.2%).

  19. Zhuqing Liu, Xin Zhang, Jia Liu, Zhengyuan Zhu, and Songtao Lu, "PILOT: An O(1/T)-Convergent Approach for Policy Evaluation with Nonlinear Function Approximation," in Proc. ICLR, Vienna, Austria, May 2024 (Spotlight Presentation, spotlight rate: 5%, acceptance rate: 31%).

  20. FNU Hairi, Zifan Zhang, and Jia Liu, "Sample and Communication Efficient Fully Decentralized MARL Policy Evaluation via a New Approach: Local TD Update," in Proc. ACM AAMAS, Auckland, New Zealand, May 2024 (acceptance rate: 25%).

  21. Haibo Yang, Zhuqing Liu, Jia Liu, Chaosheng Dong, and Michinari Momma "Federated Multi-Objective Learning," in Proc. NeurIPS, New Orleans, LA, Dec. 2023 (acceptance rate: 26.1%).

  22. Zhuqing Liu, Xin Zhang, Songtao Lu, and Jia Liu, "PRECISION: Decentralized Constrained Min-Max Learning with Low Communication and Sample Complexities," in Proc. ACM MobiHoc, Washington, DC, Oct. 2023 (acceptance rate: 21.9%).

  23. Tianchen Zhou, Michinari Momma, Chaosheng Dong, Fan Yang, Chenghuan Guo, Jin Shang, and Jia Liu, "Multi-Task Learning on Heterogeneous Graph Neural Network for Substitute Recommendation," in Proc. KDD Workshop on Mining and Learning with Graphs, (MLG), Long Beach, CA, Aug. 2023.

  24. Moyan Li, Jinmiao Fu, Shaoyuan Xu, Huidong Liu, Jia Liu, and Bryan Wang, "Hierarchical Conditional Image-to-Image Translation for Multi-Task Image Defect Correction on Shopping Websites," in Proc. ICIP, Kuala Lumpur, Malaysia, Oct. 2023.

  25. Zhuqing Liu, Xin Zhang, Prashant Khanduri, Songtao Lu, and Jia Liu, "Prometheus: Taming Sample and Communication Complexities in Constrained Decentralized Stochastic Bilevel Learning," in Proc. ICML, Honolulu, HI, Jul. 2023 (acceptance rate: 27.9%).

  26. Prashant Khanduri, Ioannis Tsaknakis, Yihua Zhang, Jia Liu, Sijia Liu, Jiawei Zhang, and Mingyi Hong, "Linearly Constrained Bilevel Optimization: A Smoothed Implicit Gradient Approach," in Proc. ICML, Honolulu, HI, Jul. 2023 (acceptance rate: 27.9%).

  27. Peiwen Qiu, Yining Li, Zhuqing Liu, Prashant Khanduri, Jia Liu, Ness B. Shroff, Elizabeth S. Bentley, and Kurt Turck, "DIAMOND: Taming Sample and Communication Complexities in Decentralized Bilevel Optimization," in Proc. IEEE INFOCOM, New York City, NY, May 2023 (acceptance rate: 19.2%).

  28. Sen Lin, Ming Shi, Anish Arora, Raef Bassily, Elisa Bertino, Constantine Caramanis, Kaushik Chowdhury, Eylem Ekici, Atilla Eryilmaz, Stratis Ioannidis, Nan Jiang, Gauri Joshi, Jim Kurose, Yingbin Liang, Zhiqiang Lin, Jia Liu, Mingyan Liu, Tommaso Melodia, Aryan Mokhtari, Rob Nowak, Sewoong Oh, Srini Parthasarathy, Chunyi Peng, Hulya Seferoglu, Ness Shroff, Sanjay Shakkottai, Kannan Srinivasan, Ameet Talwalkar, Aylin Yener and Lei Ying, "Leveraging Synergies Between AI and Networking to Build Next Generation Edge Networks," in Proc. IEEE International Conference on Collaboration and Internet Computing (CIC), Virtual, Dec. 2022.

  29. Haibo Yang, Peiwen Qiu, Prashant Khanduri, and Jia Liu, "With a Little Help from My Friend: Server-Aided Federated Learning with Partial Client Participation," in Proc. NeurIPS Workshop on Federated Learning: Recent Advances and New Challenges, (FL-NeurIPS'22), New Orleans, LA, Dec. 2022.

  30. Minghong Fang, Jia Liu, Neil Gong, and Elizabeth S. Bentley, "AFLGuard: Byzantine-robust Asynchronous Federated Learning," in Proc. ACM ACSAC, Austin, TX, Dec. 2022 (acceptance rate: 24.1%).

  31. Haibo Yang, Peiwen Qiu, and Jia Liu, "Taming Fat-Tailed (“Heavier-Tailed” with Potentially Infinite Variance) Noise in Federated Learning," in Proc. NeurIPS, New Orleans, LA, Dec. 2022 (acceptance rate: 25.6%).

  32. Haibo Yang, Zhuqing Liu, Xin Zhang, and Jia Liu, "SAGDA: Achieving O(ε-2) Communication Complexity in Federated Min-Max Learning," in Proc. NeurIPS, New Orleans, LA, Dec. 2022 (acceptance rate: 25.6%).

  33. Songtao Lu, Siliang Zeng, Xiaodong Cui, Mark S. Squillante, Lior Horesh, Brian Kingsbury, Jia Liu, and Mingyi Hong, "A Stochastic Linearized Augmented Lagrangian Method for Decentralized Bilevel Optimization," in Proc. NeurIPS, New Orleans, LA, Dec. 2022 (acceptance rate: 25.6%, IBM Research 2024 Pat Goldberg Memorial Best Paper Award Honorable Mention).

  34. Menglu Yu, Bo Ji, Hridesh Rajan, and Jia Liu, "On Scheduling Ring-All-Reduce Learning Jobs in Multi-Tenant GPU Clusters with Communication Contention," in Proc. ACM MobiHoc, Seoul, South Korea, Oct. 2022 (acceptance rate: 19.8%).

  35. Zhuqing Liu, Xin Zhang, Prashant Khanduri, Songtao Lu, and Jia Liu, "INTERACT: Achieving Low Sample and Communication Complexities in Decentralized Bilevel Learning over Networks," in Proc. ACM MobiHoc, Seoul, South Korea, Oct. 2022 (acceptance rate: 19.8%).

  36. Zhuqing Liu, Xin Zhang, and Jia Liu, "SYNTHESIS: A Semi-Asynchronous Path-Integrated Stochastic Gradient Method for Distributed Learning in Computing Clusters," in Proc. ACM MobiHoc, Seoul, South Korea, Oct. 2022 (acceptance rate: 19.8%).

  37. Xin Zhang, Minghong Fang, Zhuqing Liu, Haibo Yang, Jia Liu, and Zhengyuan Zhu, "NET-FLEET: Achieving Linear Convergence Speedup for Fully Decentralized Federated Learning with Heterogeneous Data," in Proc. ACM MobiHoc, Seoul, South Korea, Oct. 2022 (acceptance rate: 19.8%).

  38. Jinmiao Fu, Shaoyuan Xu, Huidong Liu, Yang Liu, Ning Xie, Chien-Chih Wang, Bryan Wang, Jia Liu, and Yi Sun, "CMA-CLIP: Cross-Modality Attention CLIP for Text-Image Classification," in Proc. IEEE ICIP, Bordeaux, France, Oct. 2022.

  39. Haibo Yang, Xin Zhang, Prashant Khanduri, and Jia Liu, "Anarchic Federated Learning," in Proc. ICML, Baltimore, MD, July 2022 (Long Oral Presentation, long oral presentation rate: 2%, acceptance rate: 21.9%).

  40. Michinari Momma, Chaosheng Dong, and Jia Liu, "A Multi-Objective / Multi-Task Learning Framework Induced by Pareto Stationarity," in Proc. ICML, Baltimore, MD, July 2022 (Spotlight Presentation, spotlight rate: 5%, acceptance rate: 21.9%).

  41. Jiayu Mao*, Haibo Yang*, Peiwen Qiu, Jia Liu, and Aylin Yener, "CHARLES: Channel-Quality-Adaptive Over-the-Air Federated Learning over Wireless Networks," in Proc. IEEE SPAWC, Oulu, Finland, June 2022 (Invited Paper).

  42. Haibo Yang, Peiwen Qiu, Jia Liu, and Aylin Yener, "Over-the-Air Federated Learning With Joint Adaptive Computation and Power Control," in Proc. IEEE ISIT, Espoo, Finland, June 2022.

  43. Minghong Fang, Jia Liu, Michinari Momma, and Yi Sun, "FairRoad: Achieving Fairness for Recommender Systems with Optimized Antidote Data," in Proc. ACM SACMAT, Virtual Event, June 2022.

  44. Fan Yang, Alireza Bagheri Garakani, Yifei Teng, Yan Gao, Jia Liu, Jingyuan Deng, and Yi Sun, "Spelling Correction Phonetics in E-Commerce Search," in Proc. of the 5th Workshop on e-Commerce and NLP at the 60th Annual Meeting of the Association for Computational Linguistics (ECNLP-ACL), Dublin, Ireland, May 2022.

  45. FNU Hairi, Jia Liu, and Songtao Lu，"Finite-Time Convergence and Sample Complexity of Multi-Agent Actor-Critic Reinforcement Learning with Average Reward," in Proc. ICLR, Virtual Event, April 2022 (Spotlight Presentation, spotlight rate: 5%, acceptance rate: 32%).

  46. Tianchen Zhou, Jia Liu, Chaosheng Dong, Yi Sun，"Bandit Learning with Joint Effect of Incentivized Sampling, Delayed Sampling Feedback, and Self-Reinforcing User Preferences," in Proc. ICLR, Virtual Event, April 2022 (acceptance rate: 32%).

  47. Prashant Khanduri, Haibo Yang, Mingyi Hong, Jia Liu, Hoi To Wai, Sijia Liu，"Decentralized Learning for Overparameterized Problems: A Multi-Agent Kernel Approximation Approach," in Proc. ICLR, Virtual Event, April 2022 (acceptance rate: 32%).

  48. Tianxiang Gao, Hailiang Liu, Jia Liu, Hridesh Rajan, and Hongyang Gao，"A Global Convergence Theory for Deep ReLU Implicit Networks via Over-parameterization," in Proc. ICLR, Virtual Event, April 2022 (acceptance rate: 32%).

  49. Menglu Yu, Ye Tian, Bo Ji, Chuan Wu, Hridesh Rajan, and Jia Liu, "GADGET: Online Resource Optimization for Scheduling Ring-All-Reduce Learning Jobs," in Proc. IEEE INFOCOM, Virtual Event, May 2022 (acceptance rate: 19.9%).

  50. Xin Zhang, Zhuqing Liu, Jia Liu, Zhengyuan Zhu, and Songtao Lu, "Taming Communication and Sample Complexities in Decentralized Policy Evaluation for Cooperative Multi-Agent Reinforcement Learning," in Proc. NeurIPS, Virtual Event, Dec. 2021 (acceptance rate: 26%).

  51. Prashant Khanduri, Pranay Sharma, Haibo Yang, Mingyi Hong, Jia Liu, Ketan Rajawat, and Pramod Varshney, "STEM: A Stochastic Two-Sided Momentum Algorithm Achieving Near-Optimal Sample and Communication Complexities for Federated Learning," in Proc. NeurIPS, Virtual Event, Dec. 2021 (acceptance rate: 26%).

  52. Wenbo Ren, Jia Liu, and Ness B. Shroff, "Sample Complexity Bounds for Active Ranking from Multi-wise Comparisons," in Proc. NeurIPS, Virtual Event, Dec. 2021 (acceptance rate: 26%).

  53. Hongwei Zhang, Yong Guan, Ahmed Kamal, Daji Qiao, Mai Zheng, Anish Arora, Ozdal Boyraz, Brian Cox, Thomas Daniels, Matthew Darr, Doug Jacobson, Ashfaq Khokhar, Sang Kim, James Koltes, Jia Liu, Mike Luby, Larysa Nadolny, Joshua Peschel, Patrick Schnable, Anuj Sharma, Arun Somani, and Lie Tang,"ARA: A Wireless Living Lab Vision for Smart and Connected Rural Communities," in Proc. Workshop on Wireless Network Testbeds, Experimental Evaluation and Characterization (ACM WiNTECH), Virtual Event, Oct. 2021.

  54. Haibo Yang, Jia Liu, and Elizabeth S. Bentley,"CFedAvg: Achieving Efficient Communication and Fast Convergence in Non-IID Federated Learning," in Proc. IEEE/IFIP WiOpt, Virtual Event, Oct. 2021.

  55. Prashant Khanduri, Pranay Sharma, Haibo Yang, Mingyi Hong, Jia Liu, Ketan Rajawat and Pramod K. Varshney,"Achieving Optimal Sample and Communication Complexities for Non-IID Federated Learning," in Proc. ICML Workshop on Federated Learning for User Privacy and Data Confidentiality (FL-ICML'21), Virtual Event, Jul. 2021.

  56. Fengjiao Li, Jia Liu, and Bo Ji, "Federated Learning with Fair Worker Selection: A Multi-Round Submodular Maximization Approach," in Proc. IEEE MASS, Virtual Event, Oct. 2021 (acceptance rate: 28.3%).

  57. Tianchen Zhou, Jia Liu, Chaosheng Dong, and Jingyuan Deng, "Incentivized Bandit Learning with Self-Reinforcing User Preferences," in Proc. ICML, Virtual Event, Jul. 2021 (Spotlight Presentation, spotlight rate: 5%, acceptance rate: 20.4%).

  58. Xin Zhang, Jia Liu, Zhengyuan Zhu, and Elizabeth S. Bentley, "GT-STORM: Taming Sample, Communication, and Memory Complexities in Decentralized Non-Convex Learning," in Proc. ACM MobiHoc, Shanghai, China, Jul. 2021 (acceptance rate: 20.1%).

  59. Tianxiang Gao, Songtao Lu, Jia Liu, and Chris Chu, "On the Convergence of Randomized Bregman Coordinate Descent for Non-Lipschtiz Composite Problems," in Proc. IEEE ICASSP, Virtual Event, Jun. 2021.

  60. Haibo Yang, Minghong Fang, and Jia Liu, "Achieving Linear Speedup with Partial Worker Participation in Non-IID Federated Learning," in Proc. ICLR, Virtual Event, May 2021 (acceptance rate: 28.6%).

  61. Minghong Fang, Minghao Sun, Qi Li, Neil Zhenqiang Gong, Jin Tian and Jia Liu, "Data Poisoning Attacks and Defenses to Crowdsourcing Systems," in Proc. ACM WWW (TheWebConf), Virtual Event, Apr. 2021 (acceptance rate: 20.6%).

  62. Wenbo Ren, Jia Liu, and Ness Shroff, "On Logarithmic Regret for Bandits with Knapsacks," in Proc. IEEE CISS, Special Session on Online Optimization and Learning, Virtual Event, March 2021 (Invited Paper).

  63. Xiaoyu Cao*, Minghong Fang*, Jia Liu, and Neil Gong, "FLTrust: Byzantine-robust Federated Learning via Trust Bootstrapping," in Proc. NDSS, Virtual Event, Feb. 2021 (*co-primary authors, acceptance rate: 16%).

  64. Xin Zhang, Jia Liu, Zhengyuan Zhu, and Elizabeth S. Bentley, "Low Sample and Communication Complexities in Decentralized Learning: A Triple Hybrid Approach," in Proc. IEEE INFOCOM, Virtual Event, May 2021 (acceptance rate: 19.9%).

  65. Menglu Yu, Chuan Wu, Bo Ji, and Jia Liu, "A Sum-of-Ratios Multi-Dimensional-Knapsack Decomposition for DNN Resource Scheduling," in Proc. IEEE INFOCOM, Virtual Event, May 2021 (acceptance rate: 19.9%).

  66. Peizhong Ju, Xiaojun Lin, Jia Liu, "Overfitting Can Be Harmless for Basis Pursuit, But Only to a Degree," in Proc. NeurIPS, Vancouver, Canada, December 2020 (Spotlight Presentation, spotlight rate: 3% acceptance rate: 20%).

  67. Xin Zhang, Jia Liu, and Zhengyuan Zhu, "Taming Convergence for Asynchronous Stochastic Gradient Descent with Unbounded Delay in Non-Convex Learning," in Proc. IEEE CDC, Jeju Island, Korea, December 2020.

  68. Wenbo Ren, Jia Liu, and Ness B. Shroff, "The Sample Complexity of Best-K Items Selection from Pairwise Comparisons," in Proc. ICML, Vienna, Austria, July 2020 (acceptance rate: 21.8%).

  69. Haibo Yang, Xin Zhang, Minghong Fang, and Jia Liu, "Adaptive Multi-Hierarchical signSGD for Communication-Efficient Distributed Optimization," in Proc. IEEE SPAWC, Special Session on Distributed Signal Processing for Coding and Communications, Atlanta, GA, May 2020 (Invited Paper).

  70. Ye Tian, Jia Liu, and Cathy H. Xia, "MATE: A Memory-Augmented Time-Expansion Approach for Optimal Trip-Vehicle Matching and Routing in Ride-Sharing," in Proc. ACM e-Energy, Melbourne, Australia, Jun. 2020 (acceptance rate: 23%).

  71. Xin Zhang, Minghong Fang, Jia Liu, and Zhengyuan Zhu, "Private and Communication-Efficient Edge Learning: A Sparse Differential Gaussian-Masking Distributed SGD Approach," in Proc. ACM MobiHoc, Shanghai, China, Oct. 2020 (acceptance rate: 15%).

  72. Zhengxiong Yuan, Bin Li, and Jia Liu, "Can We Improve Information Freshness with Predictions in Mobile Crowd-Learning?" in Proc. IEEE INFOCOM 2020 Age of Information Workshop, Toronto, Canada, Jul. 2020.

  73. Minghong Fang and Jia Liu, "Toward Low-Cost and Stable Blockchain Networks," in Proc. IEEE ICC, Dublin, Ireland, Jun. 2020.

  74. Minghong Fang, Neil Zhenqiang Gong, and Jia Liu, "Influence Function based Data Poisoning Attacks to Top-N Recommender Systems," in Proc. ACM WWW (TheWebConf), Taipei, Taiwan, Apr. 2020 (acceptance rate: 25%).

  75. Xuxi Yang, Lisen Deng, Jia Liu, Peng Wei, and Husheng Li, "Multi-Agent Autonomous Operations in Urban Air Mobility with Communication Constraints," in Proc. AIAA SciTech, Orlando, Florida, Jan. 2020.

  76. Xin Zhang, Jia Liu, Zhengyuan Zhu, and Elizabeth Bentley, "Communication-Efficient Network-Distributed Optimization with Differential-Coded Compressors," in Proc. IEEE INFOCOM, Toronto, Canada, Jul. 2020 (acceptance rate: 19.8%).

  77. Zhida Qin, Xiaoying Gan, Jia Liu, Hongqiu Wu, Haimin Jin, and Luoyi Fu, "Exploring Best Arm with Top Reward-Cost Ratio in Stochastic Bandits," in Proc. IEEE INFOCOM, Toronto, Canada, Jul. 2020 (acceptance rate: 19.8%).

  78. Wenbo Ren, Jia Liu, and Ness B. Shroff, "On Sample Complexity Upper and Lower Bounds for Exact Ranking from Noisy Comparisons," in Proc. NeurIPS, Vancouver, Canada, Dec. 2019 (acceptance rate: 21%).

  79. Haibo Yang, Xin Zhang, Minghong Fang, and Jia Liu, "Byzantine-Resilient Stochastic Gradient Descent for Distributed Learning: A Lipschitz-Inspired Coordinate-wise Median Approach," in Proc. IEEE CDC, Nice, France, Dec. 2019.

  80. Bin Li* and Jia Liu*, "Can We Achieve Fresh Information with Selfish Users in Mobile Crowd-Learning?" in Proc. IEEE/IFIP WiOpt, Avignon, France, Jun. 2019 (*Co-primary authors).

  81. Wenbo Ren, Jia Liu, and Ness B. Shroff, "Exploring k out of Top ρ Fraction of Arms in Stochastic Bandits," in Proc. AISTATS, Naha, Okinawa, Japan, Apr. 2019 (acceptance rate: 32.4%).

  82. Xin Zhang, Jia Liu, Zhengyuan Zhu, and Elizabeth Bentley, "Compressed Distributed Gradient Descent: Communication-Efficient Consensus over Networks," in Proc. IEEE INFOCOM, Paris, France, Apr. 2019 (acceptance rate: 19.6%).

  83. Fengjiao Li, Jia Liu, and Bo Ji, "Combinatorial Sleeping Bandits with Fairness Constraints," in Proc. IEEE INFOCOM, Paris, France, Apr. 2019 (acceptance rate: 19.6%, Best Paper Award, and Best-in-Session Presentation Award).

  84. Minghong Fang, Guolei Yang, Neil Zhenqiang Gong, and Jia Liu, "Poisoning Attacks to Graph-Based Recommender Systems," in Proc. ACM Annual Computer Security Applications Conference (ACM ACSAC), San Juan, Puerto Rico, Dec. 2018 (acceptance rate: 20.1%).

  85. Hongsen Shi*, Jia Liu*, and Qian Chen, "HVAC Precooling Optimization for Green Buildings: An RC-Network Approach," in Proc. ACM e-Energy, Karlsruhe, Germany, June 2018 (*Co-primary authors, acceptance rate: 21.9%).

  86. Bin Li, Bo Ji, and Jia Liu, "Efficient and Low-Overhead Uplink Scheduling for Large-Scale Wireless Internet-of-Things," in Proc. IEEE/IFIP WiOpt, Shanghai, China, May 2018.

  87. Jia Liu, "High-Order Momentum: Improving Latency and Convergence for Wireless Network Optimization," in Proc. IEEE INFOCOM, Honolulu, HI, Apr. 2018 (acceptance rate: 19%).

  88. Jia Liu and Elizabeth S. Bentley, "Hybrid-Beamforming-Based Millimeter-Wave Cellular Network Optimization," in Proc. IEEE/IFIP WiOpt, Paris, France, May 2017 (Best Paper Award Finalist, acceptance rate: 33%).

  89. Kuangyu Zheng, Xiaorui Wang, and Jia Liu, "DISCO: Distributed Traffic Flow Consolidation for Power Efficient Data Center Network," in Proc. IFIP Networking, Stockholm, Sweden, Jun. 2017 (acceptance rate: 28%).

  90. Jia Liu, Atilla Eryilmaz, Ness B. Shroff, and Elizabeth S. Bentley, "Heavy-Ball: A New Approach for Taming Delay and Convergence in Wireless Network Optimization," in Proc. IEEE INFOCOM, San Francisco, CA, Apr. 2016 (Best Paper Award, acceptance rate: 17%).

  91. Jia Liu, "Achieving Low-Delay and Fast-Convergence in Stochastic Network Optimization: A Nesterovian Approach," in Proc. ACM SIGMETRICS, Antibes Juan-les-Pins, Jun. 2016 (acceptance rate: 13%).

  92. Jia Liu, Atilla Eryilmaz, Ness B. Shroff, and Elizabeth S. Bentley, "Understanding the Impact of Limited Channel State Information on Massive MIMO Network Performances," in Proc. ACM MobiHoc, Paderborn, Germany, July 2016 (acceptance rate: 17%).

  93. Jia Liu, Cathy H. Xia, Ness B. Shroff, and H. D. Sherali, "A Second-Order Approach for Distributed Load Shedding in Power Systems Post-Disaster Recovery," in Proc. ACM SIGMETRICS, Austin, TX, Jun. 2014 (short paper).

  94. Jia Liu, Cathy H. Xia, Ness B. Shroff, and H. D. Sherali, "Distributed Cross-Layer Optimization in Wireless Networks: A Second-Order Approach," in Proc. IEEE INFOCOM, Turin, Italy, Apr. 14-19, 2013 (Best Paper Runner-up Award, acceptance rate: 17%).

  95. Jia Liu, Tianyou Kou, Qian Chen, and Hanif D. Sherali, "On Wireless Network Infrastructure Optimization for Cyber-Physical Systems in Future Smart Buildings," in Proc. WASA'12, Yellow Mountains, China, Aug. 8-10, 2012.

  96. Jia Liu and H. D. Sherali, "A Distributed Newton's Method for Joint Multi-Hop Routing and Flow Control: Theory and Algorithm," in Proc. IEEE INFOCOM, Orlando, FL, Mar 25-30, 2012 (acceptance rate: 18%).

  97. Jia Liu, Qian Chen, and H. D. Sherali, "Algorithm Design for Femtocell Base Station Placement in Commercial Building Environments," in Proc. IEEE INFOCOM, Orlando, FL, Mar 25-30, 2012 (acceptance rate: 18%).

  98. Yi Shi, Jia Liu, Canming Jiang, Cunhao Gao, and Y. Thomas Hou, "An optimal link layer model for multi-hop MIMO networks," in Proc. IEEE INFOCOM, Shanghai, China, Apr 10-15, 2011 (Best Paper Runner-up Award, acceptance rate: 15%).

  99. Jia Liu, Yi Shi, and Y. Thomas Hou, "A Tractable and Accurate Cross-Layer Model for Multi-Hop MIMO Ad Hoc Networks," in Proc. IEEE INFOCOM, San Diego, CA, Mar 15-19, 2010 (acceptance rate: 18%).

  100. Sushant Sharma, Yi Shi, Jia Liu, Y. Thomas Hou, and Sastr Kompella, "Is Network Coding Always Good for Cooperative Communications?," in Proc. IEEE INFOCOM, San Diego, CA, Mar 15-19, 2010 (acceptance rate: 18%).

  101. Jia Liu, Y. Thomas Hou, Yi Shi, and H. D. Sherali, "On Performance Optimization for Multi-Carrier MIMO Ad Hoc Networks," in Proc. ACM MobiHoc, New Orleans, LA, May 19-21, 2009 (acceptance rate: 18%).

  102. Yi Shi, Y. Thomas Hou, Jia Liu, and H. D. Sherali, "How to correctly use the protocol interference model for multi-hop wireless networks," in Proc. ACM MobiHoc, New Orleans, LA, May 19-21, 2009 (acceptance rate: 18%).

  103. Jia Liu, Y. Thomas Hou, and H. D. Sherali, "Optimal Power Allocation for Achieving Perfect Secrecy Capacity in MIMO Wire-Tap Channels," in Proc. CISS, Baltimore, MD, Mar 18-20, 2009.

  104. Jia Liu and Y. Thomas Hou, "On the Performance of MIMO-Based Ad Hoc Networks under Imperfect CSI," in Proc. IEEE MILCOM, San Diego, CA, Nov 17 - 19, 2008 (acceptance rate: 27%).

  105. Jia Liu and Y. Thomas Hou, "Maximum Weighted Sum Rate of Multi-Antenna Broadcast Channels," in Proc. IEEE ICC, Beijing, China, May 19 - 23, 2008 (acceptance rate: 27%).

  106. Jia Liu, Y. Thomas Hou, and H. D. Sherali, "Cross-Layer Optimization for MIMO-Based Mesh Networks with Dirty Paper Coding," in Proc. IEEE ICC, Beijing, China, May 19 - 23, 2008 (Best Paper Award, acceptance rate: 27%).

  107. Jia Liu and Y. Thomas Hou, "Weighted Proportonal Fairness Capacity of Gaussian MIMO Broadcast Channels," in Proc. IEEE INFOCOM, Phoenix, AZ, Apr. 13 - 17, 2008.

  108. Jia Liu, Y. Thomas Hou, and H. D. Sherali, "Conjugate Gradient Projection Approach for Multi-Antenna Gaussian Broadcast Channels," in Proc. IEEE ISIT, Nice, France, Jun. 24 - 29, 2007.

  109. Jia Liu, T. Y. Park, Y. Thomas Hou, Y. Shi, and H. D. Sherali, "Cross-Layer Optimization of MIMO-Based Mesh Networks Under Orthogonal Channels," in Proc. IEEE WCNC, Hong Kong, Mar. 11 - 15, 2007.

  110. Jia Liu, Y. Thomas Hou, Y. Shi, and H. D. Sherali, "Optimization of Multiuser MIMO Networks with Interference," in Proc. IEEE GLOBECOM, San Franscisco, Nov. 27 - Dec. 1, 2006.

  111. Jia Liu and A. Annamalai, "Efficacy of Channel Aware Routing Strategies in Wireless Ad Hoc Networks," in Proc. IEEE VTC, Dallas, Oct. 2005.

  112. Jia Liu and A. Annamalai, "Channel-Aware Routing Protocol for Ad Hoc Networks: Generalized Multiple-Route Path Selection Diversity," in Proc. IEEE VTC, Dallas, Oct. 2005.

  113. A. Annamalai and Jia Liu, "A Cross-Layer Design Perspective for Multi-Resolution Signaling," in Proc. IEEE GLOBECOM, Dallas, Nov. 2004.

  114. Jia Liu and A. Annamalai, "Multi-Resolution Signaling for Multimedia Multicasting," in Proc. IEEE VTC, Los Angeles, Sep. 2004.
 
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