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ORCIDJia Liu 0002
Person information
- affiliation: Iowa State University, Department of Computer Science, Ames, IA, USA
- affiliation: The Ohio State University, Department of Electrical and Computer Engineering, Columbus, OH, USA
- affiliation (PhD 2010): Virginia Tech, Bradley Department of Electrical and Computer Engineering, Blacksburg, VA, USA
Other persons with the same name
- Jia Liu — disambiguation page
- Jia Liu 0001 — Tsinghua University, Beijing National Research Center for Information Science and Technology, Beijing, China (and 1 more)
- Jia Liu 0003
![[0000-0001-7094-9324]](https://dblp.org/img/orcid-mark.12x12.png "0000-0001-7094-9324")
— University of Surrey, 5G Innovation Centre, UK (and 1 more) - Jia Liu 0004 — Anhui University of Finance and Economics, Bengbu, China
- Jia Liu 0005 — Xi'an Jiaotong University, State Key Laboratory of Electrical Insulation and Power Equipment, China (and 1 more)
- Jia Liu 0006 — North University of China, Key Laboratory of Instrumentation Science & Dynamic Measurement, Taiyuan, China
- Jia Liu 0007 — Chinese Academy of Science, Shenzhen Institutes of Advanced Technology, Guangdong Provincial Key Lab of Robotics and Intelligent System, China
- Jia Liu 0008 — Nanjing University, State Key Laboratory for Novel Software Technology, China
- Jia Liu 0009 — National Institute of Informatics, Cyber Security Research Center, Tokyo, Japan (and 2 more)
- Jia Liu 0010 — Tsinghua University, Department of Biomedical Engineering, School of Medicine, Beijing, China
- Jia Liu 0011 — Shenzhen University, College of Electronic Science and Technology, China
- Jia Liu 0012 — Jilin Engineering Normal University, School of Information Engineering, Changchun, China
- Jia Liu 0013 — Hong Kong University of Science and Technology, Business School, Hong Kong
- Jia Liu 0014 — Chinese Academy of Sciences, Xi'an Institute of Optics and Precision Mechanics, Laboratory of Remote Sensing and Intelligent information System, Xi'an, China
- Jia Liu 0015 — Nanjing University, Software Institute, Nanjing, China
- Jia Liu 0016 — Engineering University of People Armed Police Force, Xi'an, China
- Jia Liu 0017 — Chinese Academy of Sciences, Shenzhen Institutes of Advanced Technology, Laboratory of Engineering and Scientific Computing, Shenzhen, China (and 1 more)
- Jia Liu 0018 — Newcastle University Business School, Newcastle upon Tyne, UK
- Jia Liu 0019 — Nanjing University of Information Science and Technology, School of Automation, Nanjing, China
- Jia Liu 0020 — Nanjing University of Science and Technology, School of Computer Science and Engineering, China (and 1 more)
- Jia Liu 0021 — China University of Geosciences, School of Computer Science, Wuhan, China (and 3 more)
- Jia Liu 0022 — Chinese Academy of Sciences, Institute of Remote Sensing and Digital Earth, State Key Laboratory Of Remote Sensing Sciences, Beijing, China
- Jia Liu 0023 — Tsinghua University, Department of Computer Science and Technology, TNList, Beijing, China
- Jia Liu 0024 — Tsinghua University, Department of Computer Science and Technology, TNList, Beijing, China
- Jia Liu 0025 — Wuhan University of Technology, School of Computer Science and Technology, Wuhan, China (and 1 more)
- Jia Liu 0026 — Tsinghua University, Department of Electronic Engineering, TNList, Beijing, China
- Jia Liu 0027 — Chinese Academy of Agricultural Sciences, Institute of Agricultural Resources and Regional Planning, Beijing, China
- Jia Liu 0028 — Chongqing University of Posts and Telecommunications, School of Communication and Information Engineering, Chongqing, China
- Jia Liu 0029 — Beijing University of Posts and Telecommunications, Key Laboratory of Universal Wireless Communications, Beijing, China
- Jia Liu 0030 — Zhejiang University, College of Computer Science, Hangzhou, China
- Jia Liu 0031 — Zhongnan University of Economics and Law, School of Information and Safety Engineering, Wuhan, China (and 1 more)
- Jia Liu 0032 — Dalian University of Technology, School of Civil and Hydraulic Engineering, Dalian, China
- Jia Liu 0033 — Southwest Jiaotong University, School of Computing and Artificial Intelligence, Sichuan, China (and 1 more)
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2020 – today
- 2025
[i59]Ziyue Luo, Jia Liu, Myungjin Lee, Ness B. Shroff:
Prediction-Assisted Online Distributed Deep Learning Workload Scheduling in GPU Clusters. CoRR abs/2501.05563 (2025)- [i58]Mingdai Yang, Fan Yang, Yanhui Guo, Shaoyuan Xu, Tianchen Zhou, Yetian Chen, Simone Shao, Jia Liu, Yan Gao:
PCL: Prompt-based Continual Learning for User Modeling in Recommender Systems. CoRR abs/2502.19628 (2025) - 2024
- [c88]Minghong Fang, Zifan Zhang, Hairi, Prashant Khanduri, Jia Liu, Songtao Lu, Yuchen Liu, Neil Gong:
Byzantine-Robust Decentralized Federated Learning. CCS 2024: 2874-2888 - [c87]Zhuqing Liu, Xin Zhang, Jia Liu, Zhengyuan Zhu, Songtao Lu:
PILOT: An $\mathcal{O}(1/K)$-Convergent Approach for Policy Evaluation with Nonlinear Function Approximation. ICLR 2024 - [c86]Haibo Yang, Peiwen Qiu, Prashant Khanduri, Minghong Fang, Jia Liu:
Understanding Server-Assisted Federated Learning in the Presence of Incomplete Client Participation. ICML 2024 - [c85]Tianchen Zhou, 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. ICML 2024 - [c84]Peizhong Ju, Haibo Yang, Jia Liu, Yingbin Liang, Ness B. Shroff:
Can We Theoretically Quantify the Impacts of Local Updates on the Generalization Performance of Federated Learning? MobiHoc 2024: 141-150 - [i57]Haibo Yang, Peiwen Qiu, Prashant Khanduri, Minghong Fang, Jia Liu:
Understanding Server-Assisted Federated Learning in the Presence of Incomplete Client Participation. CoRR abs/2405.02745 (2024) - [i56]Tianchen Zhou, 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. CoRR abs/2405.03082 (2024) - [i55]Minghong Fang, Zifan Zhang, Hairi, Prashant Khanduri, Jia Liu, Songtao Lu, Yuchen Liu, Neil Zhenqiang Gong:
Byzantine-Robust Decentralized Federated Learning. CoRR abs/2406.10416 (2024) - [i54]Peizhong Ju, Haibo Yang, Jia Liu, Yingbin Liang, Ness B. Shroff:
Can We Theoretically Quantify the Impacts of Local Updates on the Generalization Performance of Federated Learning? CoRR abs/2409.03863 (2024) - [i53]Hairi, Minghong Fang, Zifan Zhang, Alvaro Velasquez, Jia Liu:
On the Hardness of Decentralized Multi-Agent Policy Evaluation under Byzantine Attacks. CoRR abs/2409.12882 (2024) - [i52]Jin Du, Xinhe Zhang, Hao Shen, Xun Xian, Ganghua Wang, Jiawei Zhang, Yuhong Yang, Na Li, Jia Liu, Jie Ding:
Drift to Remember. CoRR abs/2409.13997 (2024) - 2023
- [j19]Xiaowen Chu, Shadi Ibrahim, Jia Liu, Shiqiang Wang, Chuan Wu, Rongfei Zeng:
Guest Editorial: Interplay Between Machine Learning and Networking Systems. IEEE Netw. 37(4): 72-73 (2023) - [c83]Prashant Khanduri, Ioannis C. Tsaknakis, Yihua Zhang, Jia Liu, Sijia Liu, Jiawei Zhang, Mingyi Hong:
Linearly Constrained Bilevel Optimization: A Smoothed Implicit Gradient Approach. ICML 2023: 16291-16325 - [c82]Zhuqing Liu, Xin Zhang, Prashant Khanduri, Songtao Lu, Jia Liu:
Prometheus: Taming Sample and Communication Complexities in Constrained Decentralized Stochastic Bilevel Learning. ICML 2023: 22420-22453 - [c81]Peiwen Qiu, Yining Li, Zhuqing Liu, Prashant Khanduri, Jia Liu, Ness B. Shroff, Elizabeth Serena Bentley, Kurt A. Turck:
DIAMOND: Taming Sample and Communication Complexities in Decentralized Bilevel Optimization. INFOCOM 2023: 1-10 - [c80]Zhuqing Liu, Xin Zhang, Songtao Lu, Jia Liu:
PRECISION: Decentralized Constrained Min-Max Learning with Low Communication and Sample Complexities. MobiHoc 2023: 191-200 - [c79]Haibo Yang, Zhuqing Liu, Jia Liu, Chaosheng Dong, Michinari Momma:
Federated Multi-Objective Learning. NeurIPS 2023 - [i51]Zhuqing Liu, Xin Zhang, Songtao Lu, Jia Liu:
PRECISION: Decentralized Constrained Min-Max Learning with Low Communication and Sample Complexities. CoRR abs/2303.02532 (2023) - [i50]Haibo Yang, Zhuqing Liu, Jia Liu, Chaosheng Dong, Michinari Momma:
Federated Multi-Objective Learning. CoRR abs/2310.09866 (2023) - [i49]Tianchen Zhou, Jia Liu, Yang Jiao, Chaosheng Dong, Yetian Chen, Yan Gao, Yi Sun:
Bandit Learning to Rank with Position-Based Click Models: Personalized and Equal Treatments. CoRR abs/2311.04528 (2023) - 2022
- [j18]Kuangyu Zheng, Xiaorui Wang, Jia Liu:
Distributed Traffic Flow Consolidation for Power Efficiency of Large-Scale Data Center Network. IEEE Trans. Cloud Comput. 10(2): 996-1007 (2022) - [j17]Menglu Yu, Jia Liu, Chuan Wu, Bo Ji, Elizabeth S. Bentley:
Toward Efficient Online Scheduling for Distributed Machine Learning Systems. IEEE Trans. Netw. Sci. Eng. 9(4): 1951-1969 (2022) - [j16]Hongsen Shi, Jia Liu, Qian Chen:
An RC-Network Approach for HVAC Precooling Optimization in Buildings. IEEE Trans. Sustain. Comput. 7(3): 512-526 (2022) - [c78]Minghong Fang, Jia Liu, Neil Zhenqiang Gong, Elizabeth S. Bentley:
AFLGuard: Byzantine-robust Asynchronous Federated Learning. ACSAC 2022: 632-646 - [c77]Sen Lin, Ming Shi, Anish Arora, Raef Bassily, Elisa Bertino, Constantine Caramanis, Kaushik R. 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 B. Shroff, Sanjay Shakkottai, Kannan Srinivasan, Ameet Talwalkar, Aylin Yener, Lei Ying:
Leveraging Synergies Between AI and Networking to Build Next Generation Edge Networks. CIC 2022: 16-25 - [c76]Tianxiang Gao, Hailiang Liu, Jia Liu, Hridesh Rajan, Hongyang Gao:
A global convergence theory for deep ReLU implicit networks via over-parameterization. ICLR 2022 - [c75]Hairi, Jia Liu, Songtao Lu:
Finite-Time Convergence and Sample Complexity of Multi-Agent Actor-Critic Reinforcement Learning with Average Reward. ICLR 2022 - [c74]Prashant Khanduri, Haibo Yang, Mingyi Hong, Jia Liu, Hoi-To Wai, Sijia Liu:
Decentralized Learning for Overparameterized Problems: A Multi-Agent Kernel Approximation Approach. ICLR 2022 - [c73]Tianchen Zhou, Jia Liu, Chaosheng Dong, Yi Sun:
Bandit Learning with Joint Effect of Incentivized Sampling, Delayed Sampling Feedback, and Self-Reinforcing User Preferences. ICLR 2022 - [c72]Michinari Momma, Chaosheng Dong, Jia Liu:
A Multi-objective / Multi-task Learning Framework Induced by Pareto Stationarity. ICML 2022: 15895-15907 - [c71]Haibo Yang, Xin Zhang, Prashant Khanduri, Jia Liu:
Anarchic Federated Learning. ICML 2022: 25331-25363 - [c70]Menglu Yu, Ye Tian, Bo Ji, Chuan Wu, Hridesh Rajan, Jia Liu:
GADGET: Online Resource Optimization for Scheduling Ring-All-Reduce Learning Jobs. INFOCOM 2022: 1569-1578 - [c69]Haibo Yang, Peiwen Qiu, Jia Liu, Aylin Yener:
Over-the-Air Federated Learning with Joint Adaptive Computation and Power Control. ISIT 2022: 1259-1264 - [c68]Menglu Yu, Bo Ji, Hridesh Rajan, Jia Liu:
On scheduling ring-all-reduce learning jobs in multi-tenant GPU clusters with communication contention. MobiHoc 2022: 21-30 - [c67]Zhuqing Liu, Xin Zhang, Prashant Khanduri, Songtao Lu, Jia Liu:
INTERACT: achieving low sample and communication complexities in decentralized bilevel learning over networks. MobiHoc 2022: 61-70 - [c66]Xin Zhang, Minghong Fang, Zhuqing Liu, Haibo Yang, Jia Liu, Zhengyuan Zhu:
NET-FLEET: achieving linear convergence speedup for fully decentralized federated learning with heterogeneous data. MobiHoc 2022: 71-80 - [c65]Zhuqing Liu, Xin Zhang, Jia Liu:
SYNTHESIS: a semi-asynchronous path-integrated stochastic gradient method for distributed learning in computing clusters. MobiHoc 2022: 151-160 - [c64]Songtao Lu, Siliang Zeng, Xiaodong Cui, Mark S. Squillante, Lior Horesh, Brian Kingsbury, Jia Liu, Mingyi Hong:
A Stochastic Linearized Augmented Lagrangian Method for Decentralized Bilevel Optimization. NeurIPS 2022 - [c63]Haibo Yang, Zhuqing Liu, Xin Zhang, Jia Liu:
SAGDA: Achieving $\mathcal{O}(\epsilon^{-2})$ Communication Complexity in Federated Min-Max Learning. NeurIPS 2022 - [c62]Haibo Yang, Peiwen Qiu, Jia Liu:
Taming Fat-Tailed ("Heavier-Tailed" with Potentially Infinite Variance) Noise in Federated Learning. NeurIPS 2022 - [c61]Minghong Fang, Jia Liu, Michinari Momma, Yi Sun:
FairRoad: Achieving Fairness for Recommender Systems with Optimized Antidote Data. SACMAT 2022: 173-184 - [c60]Jiayu Mao, Haibo Yang, Peiwen Qiu, Jia Liu, Aylin Yener:
CHARLES: Channel-Quality-Adaptive Over-the-Air Federated Learning over Wireless Networks. SPAWC 2022: 1-5 - [i48]Menglu Yu, Ye Tian, Bo Ji, Chuan Wu, Hridesh Rajan, Jia Liu:
GADGET: Online Resource Optimization for Scheduling Ring-All-Reduce Learning Jobs. CoRR abs/2202.01158 (2022) - [i47]Haibo Yang, Peiwen Qiu, Jia Liu, Aylin Yener:
Over-the-Air Federated Learning with Joint Adaptive Computation and Power Control. CoRR abs/2205.05867 (2022) - [i46]Jiayu Mao, Haibo Yang, Peiwen Qiu, Jia Liu, Aylin Yener:
CHARLES: Channel-Quality-Adaptive Over-the-Air Federated Learning over Wireless Networks. CoRR abs/2205.09330 (2022) - [i45]Menglu Yu, Bo Ji, Hridesh Rajan, Jia Liu:
On Scheduling Ring-All-Reduce Learning Jobs in Multi-Tenant GPU Clusters with Communication Contention. CoRR abs/2207.07817 (2022) - [i44]Zhuqing Liu, Xin Zhang, Prashant Khanduri, Songtao Lu, Jia Liu:
INTERACT: Achieving Low Sample and Communication Complexities in Decentralized Bilevel Learning over Networks. CoRR abs/2207.13283 (2022) - [i43]Zhuqing Liu, Xin Zhang, Jia Liu:
SYNTHESIS: A Semi-Asynchronous Path-Integrated Stochastic Gradient Method for Distributed Learning in Computing Clusters. CoRR abs/2208.08425 (2022) - [i42]Xin Zhang, Minghong Fang, Zhuqing Liu, Haibo Yang, Jia Liu, Zhengyuan Zhu:
NET-FLEET: Achieving Linear Convergence Speedup for Fully Decentralized Federated Learning with Heterogeneous Data. CoRR abs/2208.08490 (2022) - [i41]Haibo Yang, Zhuqing Liu, Xin Zhang, Jia Liu:
SAGDA: Achieving O(ε-2) Communication Complexity in Federated Min-Max Learning. CoRR abs/2210.00611 (2022) - [i40]Haibo Yang, Peiwen Qiu, Jia Liu:
Taming Fat-Tailed ("Heavier-Tailed" with Potentially Infinite Variance) Noise in Federated Learning. CoRR abs/2210.00690 (2022) - [i39]Peiwen Qiu, Yining Li, Zhuqing Liu, Prashant Khanduri, Jia Liu, Ness B. Shroff, Elizabeth Serena Bentley, Kurt A. Turck:
DIAMOND: Taming Sample and Communication Complexities in Decentralized Bilevel Optimization. CoRR abs/2212.02376 (2022) - [i38]Minghong Fang, Jia Liu, Neil Zhenqiang Gong, Elizabeth S. Bentley:
AFLGuard: Byzantine-robust Asynchronous Federated Learning. CoRR abs/2212.06325 (2022) - [i37]Minghong Fang, Jia Liu, Michinari Momma, Yi Sun:
FairRoad: Achieving Fairness for Recommender Systems with Optimized Antidote Data. CoRR abs/2212.06750 (2022) - 2021
- [j15]Bin Li, Jia Liu:
Achieving Information Freshness With Selfish and Rational Users in Mobile Crowd-Learning. IEEE J. Sel. Areas Commun. 39(5): 1266-1276 (2021) - [j14]Bin Li, Jia Liu, Bo Ji:
Low-Overhead Wireless Uplink Scheduling for Large-Scale Internet-of-Things. IEEE Trans. Mob. Comput. 20(2): 577-587 (2021) - [c59]Wenbo Ren, Jia Liu, Ness B. Shroff:
On Logarithmic Regret for Bandits with Knapsacks. CISS 2021: 1-6 - [c58]Tianxiang Gao, Songtao Lu, Jia Liu, Chris Chu:
On the Convergence of Randomized Bregman Coordinate Descent for Non-Lipschitz Composite Problems. ICASSP 2021: 5549-5553 - [c57]Haibo Yang, Minghong Fang, Jia Liu:
Achieving Linear Speedup with Partial Worker Participation in Non-IID Federated Learning. ICLR 2021 - [c56]Tianchen Zhou, Jia Liu, Chaosheng Dong, Jingyuan Deng:
Incentivized Bandit Learning with Self-Reinforcing User Preferences. ICML 2021: 12824-12834 - [c55]Menglu Yu, Chuan Wu, Bo Ji, Jia Liu:
A Sum-of-Ratios Multi-Dimensional-Knapsack Decomposition for DNN Resource Scheduling. INFOCOM 2021: 1-10 - [c54]Xin Zhang, Jia Liu, Zhengyuan Zhu, Elizabeth Serena Bentley:
Low Sample and Communication Complexities in Decentralized Learning: A Triple Hybrid Approach. INFOCOM 2021: 1-10 - [c53]Fengjiao Li, Jia Liu, Bo Ji:
Federated Learning with Fair Worker Selection: A Multi-Round Submodular Maximization Approach. MASS 2021: 180-188 - [c52]Hongwei Zhang, Yong Guan, Ahmed E. Kamal, Daji Qiao, Mai Zheng, Anish Arora, Ozdal Boyraz, Brian Cox, Thomas Daniels, Matthew J. Darr, Doug Jacobson, Ashfaq Khokhar, Sang Wu Kim, James Koltes, Jia Liu, Mike Luby, Larysa Nadolny, Joshua M. Peschel, Patrick S. Schnable, Anuj Sharma, Arun Somani, Lie Tang:
ARA: A Wireless Living Lab Vision for Smart and Connected Rural Communities. WiNTECH 2021: 9-16 - [c51]Xin Zhang, Jia Liu, Zhengyuan Zhu, Elizabeth Serena Bentley:
GT-STORM: Taming Sample, Communication, and Memory Complexities in Decentralized Non-Convex Learning. MobiHoc 2021: 271-280 - [c50]Xiaoyu Cao, Minghong Fang, Jia Liu, Neil Zhenqiang Gong:
FLTrust: Byzantine-robust Federated Learning via Trust Bootstrapping. NDSS 2021 - [c49]Wenbo Ren, Jia Liu, Ness B. Shroff:
Sample Complexity Bounds for Active Ranking from Multi-wise Comparisons. NeurIPS 2021: 4290-4300 - [c48]Prashant Khanduri, Pranay Sharma, Haibo Yang, Mingyi Hong, Jia Liu, Ketan Rajawat, Pramod K. Varshney:
STEM: A Stochastic Two-Sided Momentum Algorithm Achieving Near-Optimal Sample and Communication Complexities for Federated Learning. NeurIPS 2021: 6050-6061 - [c47]Xin Zhang, Zhuqing Liu, Jia Liu, Zhengyuan Zhu, Songtao Lu:
Taming Communication and Sample Complexities in Decentralized Policy Evaluation for Cooperative Multi-Agent Reinforcement Learning. NeurIPS 2021: 18825-18838 - [c46]Haibo Yang, Jia Liu, Elizabeth S. Bentley:
CFedAvg: Achieving Efficient Communication and Fast Convergence in Non-IID Federated Learning. WiOpt 2021: 113-120 - [c45]Minghong Fang, Minghao Sun, Qi Li, Neil Zhenqiang Gong, Jin Tian, Jia Liu:
Data Poisoning Attacks and Defenses to Crowdsourcing Systems. WWW 2021: 969-980 - [i36]Haibo Yang, Minghong Fang, Jia Liu:
Achieving Linear Speedup with Partial Worker Participation in Non-IID Federated Learning. CoRR abs/2101.11203 (2021) - [i35]Minghong Fang, Minghao Sun, Qi Li, Neil Zhenqiang Gong, Jin Tian, Jia Liu:
Data Poisoning Attacks and Defenses to Crowdsourcing Systems. CoRR abs/2102.09171 (2021) - [i34]Xin Zhang, Jia Liu, Zhengyuan Zhu, Elizabeth S. Bentley:
GT-STORM: Taming Sample, Communication, and Memory Complexities in Decentralized Non-Convex Learning. CoRR abs/2105.01231 (2021) - [i33]Tianchen Zhou, Jia Liu, Chaosheng Dong, Jingyuan Deng:
Incentivized Bandit Learning with Self-Reinforcing User Preferences. CoRR abs/2105.08869 (2021) - [i32]Menglu Yu, Chuan Wu, Bo Ji, Jia Liu:
A Sum-of-Ratios Multi-Dimensional-Knapsack Decomposition for DNN Resource Scheduling. CoRR abs/2105.13855 (2021) - [i31]Haibo Yang, Jia Liu, Elizabeth S. Bentley:
CFedAvg: Achieving Efficient Communication and Fast Convergence in Non-IID Federated Learning. CoRR abs/2106.07155 (2021) - [i30]Prashant Khanduri, Pranay Sharma, Haibo Yang, Mingyi Hong, Jia Liu, Ketan Rajawat, Pramod K. Varshney:
STEM: A Stochastic Two-Sided Momentum Algorithm Achieving Near-Optimal Sample and Communication Complexities for Federated Learning. CoRR abs/2106.10435 (2021) - [i29]Fengjiao Li, Jia Liu, Bo Ji:
Federated Learning with Fair Worker Selection: A Multi-Round Submodular Maximization Approach. CoRR abs/2107.11728 (2021) - [i28]Menglu Yu, Jia Liu, Chuan Wu, Bo Ji, Elizabeth S. Bentley:
Toward Efficient Online Scheduling for Distributed Machine Learning Systems. CoRR abs/2108.02917 (2021) - [i27]Haibo Yang, Xin Zhang, Prashant Khanduri, Jia Liu:
Anarchic Federated Learning. CoRR abs/2108.09875 (2021) - [i26]Tianxiang Gao, Hailiang Liu, Jia Liu, Hridesh Rajan, Hongyang Gao:
A global convergence theory for deep ReLU implicit networks via over-parameterization. CoRR abs/2110.05645 (2021) - 2020
- [j13]Fengjiao Li, Jia Liu, Bo Ji:
Combinatorial Sleeping Bandits With Fairness Constraints. IEEE Trans. Netw. Sci. Eng. 7(3): 1799-1813 (2020) - [c44]Xin Zhang, Jia Liu, Zhengyuan Zhu:
Taming Convergence for Asynchronous Stochastic Gradient Descent with Unbounded Delay in Non-Convex Learning. CDC 2020: 3580-3585 - [c43]Ye Tian, Jia Liu, Cathy H. Xia:
MATE: A Memory-Augmented Time-Expansion Approach for Optimal Trip-Vehicle Matching and Routing in Ride-Sharing. e-Energy 2020: 133-143 - [c42]Minghong Fang, Jia Liu:
Toward Low-Cost and Stable Blockchain Networks. ICC 2020: 1-6 - [c41]Wenbo Ren, Jia Liu, Ness B. Shroff:
The Sample Complexity of Best-k Items Selection from Pairwise Comparisons. ICML 2020: 8051-8072 - [c40]Xin Zhang, Jia Liu, Zhengyuan Zhu, Elizabeth S. Bentley:
Communication-Efficient Network-Distributed Optimization with Differential-Coded Compressors. INFOCOM 2020: 317-326 - [c39]Zhengxiong Yuan, Bin Li, Jia Liu:
Can We Improve Information Freshness with Predictions in Mobile Crowd-Learning? INFOCOM Workshops 2020: 702-709 - [c38]Xin Zhang, Minghong Fang, Jia Liu, Zhengyuan Zhu:
Private and communication-efficient edge learning: a sparse differential gaussian-masking distributed SGD approach. MobiHoc 2020: 261-270 - [c37]Peizhong Ju, Xiaojun Lin, Jia Liu:
Overfitting Can Be Harmless for Basis Pursuit, But Only to a Degree. NeurIPS 2020 - [c36]Haibo Yang, Xin Zhang, Minghong Fang, Jia Liu:
Adaptive Multi-Hierarchical signSGD for Communication-Efficient Distributed Optimization. SPAWC 2020: 1-5 - [c35]Minghong Fang, Neil Zhenqiang Gong, Jia Liu:
Influence Function based Data Poisoning Attacks to Top-N Recommender Systems. WWW 2020: 3019-3025 - [i25]Xin Zhang, Minghong Fang, Jia Liu, Zhengyuan Zhu:
Private and Communication-Efficient Edge Learning: A Sparse Differential Gaussian-Masking Distributed SGD Approach. CoRR abs/2001.03836 (2020) - [i24]Tianxiang Gao, Songtao Lu, Jia Liu, Chris Chu:
Randomized Bregman Coordinate Descent Methods for Non-Lipschitz Optimization. CoRR abs/2001.05202 (2020) - [i23]Peizhong Ju, Xiaojun Lin, Jia Liu:
Overfitting Can Be Harmless for Basis Pursuit: Only to a Degree. CoRR abs/2002.00492 (2020) - [i22]Minghong Fang, Neil Zhenqiang Gong, Jia Liu:
Influence Function based Data Poisoning Attacks to Top-N Recommender Systems. CoRR abs/2002.08025 (2020) - [i21]Minghong Fang, Jia Liu:
Toward Low-Cost and Stable Blockchain Networks. CoRR abs/2002.08027 (2020) - [i20]Wenbo Ren, Xingyu Zhou, Jia Liu, Ness B. Shroff:
Multi-Armed Bandits with Local Differential Privacy. CoRR abs/2007.03121 (2020) - [i19]Wenbo Ren, Jia Liu, Ness B. Shroff:
The Sample Complexity of Best-k Items Selection from Pairwise Comparisons. CoRR abs/2007.03133 (2020) - [i18]Xiaoyu Cao, Minghong Fang, Jia Liu, Neil Zhenqiang Gong:
FLTrust: Byzantine-robust Federated Learning via Trust Bootstrapping. CoRR abs/2012.13995 (2020)
2010 – 2019
- 2019
- [j12]Jia Liu, Elizabeth S. Bentley:
Hybrid-Beamforming-Based Millimeter-Wave Cellular Network Optimization. IEEE J. Sel. Areas Commun. 37(12): 2799-2813 (2019) - [c34]Wenbo Ren, Jia Liu, Ness B. Shroff:
Exploring k out of Top $ρ$ Fraction of Arms in Stochastic Bandits. AISTATS 2019: 2820-2828 - [c33]Haibo Yang, Xin Zhang, Minghong Fang, Jia Liu:
Byzantine-Resilient Stochastic Gradient Descent for Distributed Learning: A Lipschitz-Inspired Coordinate-wise Median Approach. CDC 2019: 5832-5837 - [c32]Fengjiao Li, Jia Liu, Bo Ji:
Combinatorial Sleeping Bandits with Fairness Constraints. INFOCOM 2019: 1702-1710 - [c31]Xin Zhang, Jia Liu, Zhengyuan Zhu, Elizabeth S. Bentley:
Compressed Distributed Gradient Descent: Communication-Efficient Consensus over Networks. INFOCOM 2019: 2431-2439 - [c30]Wenbo Ren, Jia Liu, Ness B. Shroff:
On Sample Complexity Upper and Lower Bounds for Exact Ranking from Noisy Comparisons. NeurIPS 2019: 10014-10024 - [c29]Bin Li, Jia Liu:
Can We Achieve Fresh Information with Selfish Users in Mobile Crowd-Learning? WiOpt 2019: 1-8 - [i17]Fengjiao Li, Jia Liu, Bo Ji:
Combinatorial Sleeping Bandits with Fairness Constraints. CoRR abs/1901.04891 (2019) - [i16]Bin Li, Jia Liu:
Can We Achieve Fresh Information with Selfish Users in Mobile Crowd-Learning? CoRR abs/1902.06149 (2019) - [i15]Xin Zhang, Jia Liu, Zhengyuan Zhu:
Distributed Linear Model Clustering over Networks: A Tree-Based Fused-Lasso ADMM Approach. CoRR abs/1905.11549 (2019) - [i14]Wenbo Ren, Jia Liu, Ness B. Shroff:
On Sample Complexity Upper and Lower Bounds for Exact Ranking from Noisy Comparisons. CoRR abs/1909.03194 (2019) - [i13]Haibo Yang, Xin Zhang, Minghong Fang, Jia Liu:
Byzantine-Resilient Stochastic Gradient Descent for Distributed Learning: A Lipschitz-Inspired Coordinate-wise Median Approach. CoRR abs/1909.04532 (2019) - [i12]Xin Zhang, Jia Liu, Zhengyuan Zhu, Elizabeth S. Bentley:
Communication-Efficient Network-Distributed Optimization with Differential-Coded Compressors. CoRR abs/1912.03208 (2019) - [i11]Tianxiang Gao, Songtao Lu, Jia Liu, Chris Chu:
Leveraging Two Reference Functions in Block Bregman Proximal Gradient Descent for Non-convex and Non-Lipschitz Problems. CoRR abs/1912.07527 (2019) - 2018
- [c28]Minghong Fang, Guolei Yang, Neil Zhenqiang Gong, Jia Liu:
Poisoning Attacks to Graph-Based Recommender Systems. ACSAC 2018: 381-392 - [c27]Hongsen Shi, Jia Liu, Qian Chen:
HVAC Precooling Optimization for Green Buildings: An RC-Network Approach. e-Energy 2018: 249-260 - [c26]Jia Liu:
High-Order Momentum: Improving Latency and Convergence for Wireless Network Optimization. INFOCOM 2018: 1862-1870 - [c25]Bin Li, Bo Ji, Jia Liu:
Efficient and low-overhead uplink scheduling for large-scale wireless Internet-of-Things. WiOpt 2018: 1-8 - [i10]Hejian Sang, Jia Liu:
Adaptive Stochastic Gradient Langevin Dynamics: Taming Convergence and Saddle Point Escape Time. CoRR abs/1805.09416 (2018) - [i9]Xin Zhang, Jia Liu, Zhengyuan Zhu:
Taming Convergence for Asynchronous Stochastic Gradient Descent with Unbounded Delay in Non-Convex Learning. CoRR abs/1805.09470 (2018) - [i8]Wenbo Ren, Jia Liu, Ness B. Shroff:
PAC Ranking from Pairwise and Listwise Queries: Lower Bounds and Upper Bounds. CoRR abs/1806.02970 (2018) - [i7]Minghong Fang, Guolei Yang, Neil Zhenqiang Gong, Jia Liu:
Poisoning Attacks to Graph-Based Recommender Systems. CoRR abs/1809.04127 (2018) - [i6]Wenbo Ren, Jia Liu, Ness B. Shroff:
Exploring k out of Top ρ Fraction of Arms in Stochastic Bandits. CoRR abs/1810.11857 (2018) - [i5]Xin Zhang, Jia Liu, Zhengyuan Zhu, Elizabeth S. Bentley:
Compressed Distributed Gradient Descent: Communication-Efficient Consensus over Networks. CoRR abs/1812.04048 (2018) - 2017
- [j11]Jia Liu, Atilla Eryilmaz, Ness B. Shroff, Elizabeth S. Bentley:
Understanding the Impacts of Limited Channel State Information on Massive MIMO Cellular Network Optimization. IEEE J. Sel. Areas Commun. 35(8): 1715-1727 (2017) - [c24]Kuangyu Zheng, Xiaorui Wang, Jia Liu:
DISCO: Distributed traffic flow consolidation for power efficient data center network. Networking 2017: 1-9 - [c23]Jia Liu, Elizabeth S. Bentley:
Hybrid-beamforming-based millimeter-wave cellular network optimization. WiOpt 2017: 1-8 - 2016
- [j10]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 Trans. Netw. 24(3): 1404-1420 (2016) - [c22]Jia Liu, Atilla Eryilmaz, Ness B. Shroff, Elizabeth S. Bentley:
Heavy-ball: A new approach to tame delay and convergence in wireless network optimization. INFOCOM 2016: 1-9 - [c21]Jia Liu, Atilla Eryilmaz, Ness B. Shroff, Elizabeth S. Bentley:
Understanding the impact of limited channel state information on massive MIMO network performances. MobiHoc 2016: 251-260 - [c20]Jia Liu:
Achieving Low-Delay and Fast-Convergence in Stochastic Network Optimization: A Nesterovian Approach. SIGMETRICS 2016: 221-234 - 2015
- [j9]Jia Liu, Tianyou Kou, Qian Chen, Hanif D. Sherali:
On wireless network infrastructure optimisation for cyber-physical systems in future smart buildings. Int. J. Sens. Networks 18(3/4): 148-160 (2015) - 2014
- [j8]Yi Shi, Jia Liu, Canming Jiang, Cunhao Gao, Y. Thomas Hou:
A DoF-Based Link Layer Model for Multi-Hop MIMO Networks. IEEE Trans. Mob. Comput. 13(7): 1395-1408 (2014) - [c19]Jia Liu, Cathy H. Xia, Ness B. Shroff, Hanif D. Sherali:
Distributed optimal load shedding for disaster recovery in smart electric power grids: a second-order approach. SIGMETRICS 2014: 591-592 - 2013
- [j7]Jia Liu, Cathy H. Xia, Ness B. Shroff, Xiaodong Zhang:
On distributed computation rate optimization for deploying cloud computing programming frameworks. SIGMETRICS Perform. Evaluation Rev. 40(4): 63-72 (2013) - [j6]Yi Shi, Y. Thomas Hou, Jia Liu, Sastry Kompella:
Bridging the Gap between Protocol and Physical Models for Wireless Networks. IEEE Trans. Mob. Comput. 12(7): 1404-1416 (2013) - [c18]Jia Liu, Cathy H. Xia, Ness B. Shroff, Hanif D. Sherali:
Distributed cross-layer optimization in wireless networks: A second-order approach. INFOCOM 2013: 2103-2111 - 2012
- [j5]Jia Liu, Ness B. Shroff, Hanif D. Sherali:
Optimal Power Allocation in Multi-Relay MIMO Cooperative Networks: Theory and Algorithms. IEEE J. Sel. Areas Commun. 30(2): 331-340 (2012) - [j4]Jia Liu, Tianyou Kou, Qian Chen, Hanif D. Sherali:
Femtocell Base Station Deployment in Commercial Buildings: A Global Optimization Approach. IEEE J. Sel. Areas Commun. 30(3): 652-663 (2012) - [j3]Sushant Sharma, Yi Shi, Jia Liu, Y. Thomas Hou, Sastry Kompella, Scott F. Midkiff:
Network Coding in Cooperative Communications: Friend or Foe? IEEE Trans. Mob. Comput. 11(7): 1073-1085 (2012) - [c17]Jia Liu, Hanif D. Sherali:
A distributed Newton's method for joint multi-hop routing and flow control: Theory and algorithm. INFOCOM 2012: 2489-2497 - [c16]Jia Liu, Qian Chen, Hanif D. Sherali:
Algorithm design for femtocell base station placement in commercial building environments. INFOCOM 2012: 2951-2955 - [c15]Jia Liu, Tianyou Kou, Qian Chen, Hanif D. Sherali:
On Wireless Network Infrastructure Optimization for Cyber-Physical Systems in Future Smart Buildings. WASA 2012: 607-618 - 2011
- [c14]Yi Shi, Jia Liu, Canming Jiang, Cunhao Gao, Y. Thomas Hou:
An optimal link layer model for multi-hop MIMO networks. INFOCOM 2011: 1916-1924 - [i4]Jia Liu, Hanif D. Sherali:
A Distributed Newton Approach for Joint Multi-Hop Routing and Flow Control: Theory and Algorithm. CoRR abs/1108.1989 (2011) - 2010
- [b1]Jia Liu:
MIMO Wireless Networks: Modeling and Optimization. Virginia Tech, Blacksburg, VA, USA, 2010 - [c13]Sushant Sharma, Yi Shi, Jia Liu, Y. Thomas Hou, Sastry Kompella:
Is Network Coding Always Good for Cooperative Communications? INFOCOM 2010: 1990-1998 - [c12]Jia Liu, Yi Shi, Y. Thomas Hou:
A Tractable and Accurate Cross-Layer Model for Multi-Hop MIMO Networks. INFOCOM 2010: 2348-2356
2000 – 2009
- 2009
- [c11]Jia Liu, Y. Thomas Hou, Hanif D. Sherali:
Optimal power allocation for achieving perfect secrecy capacity in MIMO wire-tap channels. CISS 2009: 606-611 - [c10]Jia Liu, Y. Thomas Hou, Yi Shi, Hanif D. Sherali:
On performance optimization for multi-carrier MIMO ad hoc networks. MobiHoc 2009: 43-54 - [c9]Yi Shi, Y. Thomas Hou, Jia Liu, Sastry Kompella:
How to correctly use the protocol interference model for multi-hop wireless networks. MobiHoc 2009: 239-248 - 2008
- [j2]Jia Liu, Y. Thomas Hou, Yi Shi, Hanif D. Sherali:
Cross-Layer Optimization for MIMO-Based Wireless Ad Hoc Networks: Routing, Power Allocation, and Bandwidth Allocation. IEEE J. Sel. Areas Commun. 26(6): 913-926 (2008) - [j1]Jia Liu, Y. Thomas Hou, Yi Shi, Hanif D. Sherali, Sastry Kompella:
On the capacity of multiuser MIMO networks with interference. IEEE Trans. Wirel. Commun. 7(2): 488-494 (2008) - [c8]Jia Liu, Yiwei Thomas Hou, Hanif D. Sherali:
Routing and Power Allocation for MIMO-Based Ad Hoc Networks with Dirty Paper Coding. ICC 2008: 2859-2864 - [c7]Jia Liu, Yiwei Thomas Hou, Hanif D. Sherali:
On the Maximum Weighted Sum-Rate of MIMO Gaussian Broadcast Channels. ICC 2008: 3664-3668 - [c6]Jia Liu, Y. Thomas Hou:
Weighted Proportional Fairness Capacity of Gaussian MIMO Broadcast Channels. INFOCOM 2008: 385-393 - 2007
- [c5]Jia Liu, Y. Thomas Hou, Sastry Kompella, Hanif D. Sherali:
Conjugate Gradient Projection Approach for MIMO Gaussian Broadcast Channels. ISIT 2007: 781-785 - [c4]Jia Liu, Tae Yoon Park, Y. Thomas Hou, Yi Shi, Hanif D. Sherali:
Cross-Layer Optimization of MIMO-Based Mesh Networks Under Orthogonal Channels. WCNC 2007: 49-54 - [i3]Jia Liu, Y. Thomas Hou:
Cross-Layer Optimization of MIMO-Based Mesh Networks with Gaussian Vector Broadcast Channels. CoRR abs/0704.0967 (2007) - [i2]Jia Liu, Y. Thomas Hou, Hanif D. Sherali:
Conjugate Gradient Projection Approach for Multi-Antenna Gaussian Broadcast Channels. CoRR abs/cs/0701061 (2007) - [i1]Jia Liu, Y. Thomas Hou:
Maximum Weighted Sum Rate of Multi-Antenna Broadcast Channels. CoRR abs/cs/0703111 (2007) - 2006
- [c3]Jia Liu, Y. Thomas Hou, Yi Shi, Hanif D. Sherali:
Optimization of Multiuser MIMO Networks with Interference. GLOBECOM 2006 - 2004
- [c2]Annamalai Annamalai, Jia Liu:
A cross-layer design perspective for multi-resolution signaling. GLOBECOM 2004: 3342-3346 - [c1]Jia Liu, Annamalai Annamalai:
Multi-resolution signaling for multimedia multicasting. VTC Fall (2) 2004: 1088-1092
Coauthor Index
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