A cross-layer design perspective for multi-resolution signaling. - Annamalai Annamalai; Jia Liu 002 (GLOBECOM, 2004)

Multi-resolution signaling for multimedia multicasting. - Jia Liu 002; Annamalai Annamalai (VTC Fall (2), 2004)

Optimization of Multiuser MIMO Networks with Interference. - Jia Liu 002; Y. Thomas Hou 001; Yi Shi 001; Hanif D. Sherali (GLOBECOM, 2006)

Conjugate Gradient Projection Approach for MIMO Gaussian Broadcast Channels. - Jia Liu 002; Y. Thomas Hou 001; Sastry Kompella; Hanif D. Sherali (ISIT, 2007)

Cross-Layer Optimization of MIMO-Based Mesh Networks Under Orthogonal Channels. - Jia Liu 002; Tae Yoon Park; Y. Thomas Hou 001; Yi Shi 001; Hanif D. Sherali (WCNC, 2007)

Cross-Layer Optimization of MIMO-Based Mesh Networks with Gaussian Vector Broadcast Channels - Jia Liu 002; Y. Thomas Hou 001 (CoRR, 2007)

Conjugate Gradient Projection Approach for Multi-Antenna Gaussian Broadcast Channels - Jia Liu 002; Y. Thomas Hou 001; Hanif D. Sherali (CoRR, 2007)

Maximum Weighted Sum Rate of Multi-Antenna Broadcast Channels - Jia Liu 002; Y. Thomas Hou 001 (CoRR, 2007)

Routing and Power Allocation for MIMO-Based Ad Hoc Networks with Dirty Paper Coding. - Jia Liu 002; Yiwei Thomas Hou; Hanif D. Sherali (ICC, 2008)

On the Maximum Weighted Sum-Rate of MIMO Gaussian Broadcast Channels. - Jia Liu 002; Yiwei Thomas Hou; Hanif D. Sherali (ICC, 2008)

Weighted Proportional Fairness Capacity of Gaussian MIMO Broadcast Channels. - Jia Liu 002; Y. Thomas Hou 001 (INFOCOM, 2008)

Cross-Layer Optimization for MIMO-Based Wireless Ad Hoc Networks: Routing, Power Allocation, and Bandwidth Allocation. - Jia Liu 002; Y. Thomas Hou 001; Yi Shi 001; Hanif D. Sherali (IEEE J. Sel. Areas Commun., 2008)

On the capacity of multiuser MIMO networks with interference. - Jia Liu 002; Y. Thomas Hou 001; Yi Shi 001; Hanif D. Sherali; Sastry Kompella (IEEE Trans. Wirel. Commun., 2008)

Optimal power allocation for achieving perfect secrecy capacity in MIMO wire-tap channels. - Jia Liu 002; Y. Thomas Hou 001; Hanif D. Sherali (CISS, 2009)

On performance optimization for multi-carrier MIMO ad hoc networks. - Jia Liu 002; Y. Thomas Hou 001; Yi Shi 001; Hanif D. Sherali (MobiHoc, 2009)

How to correctly use the protocol interference model for multi-hop wireless networks. - Yi Shi 001; Y. Thomas Hou 001; Jia Liu 002; Sastry Kompella (MobiHoc, 2009)

A Tractable and Accurate Cross-Layer Model for Multi-Hop MIMO Networks. - Jia Liu 002; Yi Shi 001; Y. Thomas Hou 001 (INFOCOM, 2010)

Is Network Coding Always Good for Cooperative Communications? - Sushant Sharma; Yi Shi 001; Jia Liu 002; Y. Thomas Hou 001; Sastry Kompella (INFOCOM, 2010)

MIMO Wireless Networks: Modeling and Optimization. - Jia Liu 002 (2010)

An optimal link layer model for multi-hop MIMO networks. - Yi Shi 001; Jia Liu 002; Canming Jiang; Cunhao Gao; Y. Thomas Hou 001 (INFOCOM, 2011)

A Distributed Newton Approach for Joint Multi-Hop Routing and Flow Control: Theory and Algorithm - Jia Liu 002; Hanif D. Sherali (CoRR, 2011)

Algorithm design for femtocell base station placement in commercial building environments. - Jia Liu 002; Qian Chen 026; Hanif D. Sherali (INFOCOM, 2012)

A distributed Newton's method for joint multi-hop routing and flow control: Theory and algorithm. - Jia Liu 002; Hanif D. Sherali (INFOCOM, 2012)

On Wireless Network Infrastructure Optimization for Cyber-Physical Systems in Future Smart Buildings. - Jia Liu 002; Tianyou Kou; Qian Chen 026; Hanif D. Sherali (WASA, 2012)

Femtocell Base Station Deployment in Commercial Buildings: A Global Optimization Approach. - Jia Liu 002; Tianyou Kou; Qian Chen 026; Hanif D. Sherali (IEEE J. Sel. Areas Commun., 2012)

Optimal Power Allocation in Multi-Relay MIMO Cooperative Networks: Theory and Algorithms. - Jia Liu 002; Ness B. Shroff; Hanif D. Sherali (IEEE J. Sel. Areas Commun., 2012)

Network Coding in Cooperative Communications: Friend or Foe? - Sushant Sharma; Yi Shi 001; Jia Liu 002; Y. Thomas Hou 001; Sastry Kompella; Scott F. Midkiff (IEEE Trans. Mob. Comput., 2012)

Distributed cross-layer optimization in wireless networks: A second-order approach. - Jia Liu 002; Cathy H. Xia; Ness B. Shroff; Hanif D. Sherali (INFOCOM, 2013)

On distributed computation rate optimization for deploying cloud computing programming frameworks. - Jia Liu 002; Cathy H. Xia; Ness B. Shroff; Xiaodong Zhang 001 (SIGMETRICS Perform. Evaluation Rev., 2013)

Bridging the Gap between Protocol and Physical Models for Wireless Networks. - Yi Shi 001; Y. Thomas Hou 001; Jia Liu 002; Sastry Kompella (IEEE Trans. Mob. Comput., 2013)

Distributed optimal load shedding for disaster recovery in smart electric power grids: a second-order approach. - Jia Liu 002; Cathy H. Xia; Ness B. Shroff; Hanif D. Sherali (SIGMETRICS, 2014)

A DoF-Based Link Layer Model for Multi-Hop MIMO Networks. - Yi Shi 001; Jia Liu 002; Canming Jiang; Cunhao Gao; Y. Thomas Hou 001 (IEEE Trans. Mob. Comput., 2014)

On wireless network infrastructure optimisation for cyber-physical systems in future smart buildings. - Jia Liu 002; Tianyou Kou; Qian Chen 026; Hanif D. Sherali (Int. J. Sens. Networks, 2015)

Heavy-ball: A new approach to tame delay and convergence in wireless network optimization. - Jia Liu 002; Atilla Eryilmaz; Ness B. Shroff; Elizabeth S. Bentley (INFOCOM, 2016)

Understanding the impact of limited channel state information on massive MIMO network performances. - Jia Liu 002; Atilla Eryilmaz; Ness B. Shroff; Elizabeth S. Bentley (MobiHoc, 2016)

Achieving Low-Delay and Fast-Convergence in Stochastic Network Optimization: A Nesterovian Approach. - Jia Liu 002 (SIGMETRICS, 2016)

Joint Congestion Control and Routing Optimization: An Efficient Second-Order Distributed Approach. - Jia Liu 002; Ness B. Shroff; Cathy H. Xia; Hanif D. Sherali (IEEE/ACM Trans. Netw., 2016)

DISCO: Distributed traffic flow consolidation for power efficient data center network. - Kuangyu Zheng; Xiaorui Wang; Jia Liu 002 (Networking, 2017)

Understanding the Impacts of Limited Channel State Information on Massive MIMO Cellular Network Optimization. - Jia Liu 002; Atilla Eryilmaz; Ness B. Shroff; Elizabeth S. Bentley (IEEE J. Sel. Areas Commun., 2017)

Poisoning Attacks to Graph-Based Recommender Systems. - Minghong Fang; Guolei Yang; Neil Zhenqiang Gong; Jia Liu 002 (ACSAC, 2018)

HVAC Precooling Optimization for Green Buildings: An RC-Network Approach. - Hongsen Shi; Jia Liu 002; Qian Chen 026 (e-Energy, 2018)

High-Order Momentum: Improving Latency and Convergence for Wireless Network Optimization. - Jia Liu 002 (INFOCOM, 2018)

Efficient and low-overhead uplink scheduling for large-scale wireless Internet-of-Things. - Bin Li 014; Bo Ji 001; Jia Liu 002 (WiOpt, 2018)

Adaptive Stochastic Gradient Langevin Dynamics: Taming Convergence and Saddle Point Escape Time. - Hejian Sang; Jia Liu 002 (CoRR, 2018)

PAC Ranking from Pairwise and Listwise Queries: Lower Bounds and Upper Bounds. - Wenbo Ren; Jia Liu 002; Ness B. Shroff (CoRR, 2018)

Exploring k out of Top ρ Fraction of Arms in Stochastic Bandits. - Wenbo Ren; Jia Liu 002; Ness B. Shroff (CoRR, 2018)

Exploring k out of Top $ρ$ Fraction of Arms in Stochastic Bandits. - Wenbo Ren; Jia Liu 002; Ness B. Shroff (AISTATS, 2019)

Byzantine-Resilient Stochastic Gradient Descent for Distributed Learning: A Lipschitz-Inspired Coordinate-wise Median Approach. - Haibo Yang 001; Xin Zhang 054; Minghong Fang; Jia Liu 002 (CDC, 2019)

Compressed Distributed Gradient Descent: Communication-Efficient Consensus over Networks. - Xin Zhang 054; Jia Liu 002; Zhengyuan Zhu; Elizabeth S. Bentley (INFOCOM, 2019)

On Sample Complexity Upper and Lower Bounds for Exact Ranking from Noisy Comparisons. - Wenbo Ren; Jia Liu 002; Ness B. Shroff (NeurIPS, 2019)

Can We Achieve Fresh Information with Selfish Users in Mobile Crowd-Learning? - Bin Li 014; Jia Liu 002 (WiOpt, 2019)

Distributed Linear Model Clustering over Networks: A Tree-Based Fused-Lasso ADMM Approach. - Xin Zhang 054; Jia Liu 002; Zhengyuan Zhu (CoRR, 2019)

Leveraging Two Reference Functions in Block Bregman Proximal Gradient Descent for Non-convex and Non-Lipschitz Problems. - Tianxiang Gao; Songtao Lu; Jia Liu 002; Chris Chu (CoRR, 2019)

Hybrid-Beamforming-Based Millimeter-Wave Cellular Network Optimization. - Jia Liu 002; Elizabeth S. Bentley (IEEE J. Sel. Areas Commun., 2019)

Taming Convergence for Asynchronous Stochastic Gradient Descent with Unbounded Delay in Non-Convex Learning. - Xin Zhang 054; Jia Liu 002; Zhengyuan Zhu (CDC, 2020)

MATE: A Memory-Augmented Time-Expansion Approach for Optimal Trip-Vehicle Matching and Routing in Ride-Sharing. - Ye Tian; Jia Liu 002; Cathy H. Xia (e-Energy, 2020)

Toward Low-Cost and Stable Blockchain Networks. - Minghong Fang; Jia Liu 002 (ICC, 2020)

The Sample Complexity of Best-k Items Selection from Pairwise Comparisons. - Wenbo Ren; Jia Liu 002; Ness B. Shroff (ICML, 2020)

Can We Improve Information Freshness with Predictions in Mobile Crowd-Learning? - Zhengxiong Yuan; Bin Li 014; Jia Liu 002 (INFOCOM Workshops, 2020)

Communication-Efficient Network-Distributed Optimization with Differential-Coded Compressors. - Xin Zhang 054; Jia Liu 002; Zhengyuan Zhu; Elizabeth S. Bentley (INFOCOM, 2020)

Private and communication-efficient edge learning: a sparse differential gaussian-masking distributed SGD approach. - Xin Zhang 054; Minghong Fang; Jia Liu 002; Zhengyuan Zhu (MobiHoc, 2020)

Overfitting Can Be Harmless for Basis Pursuit, But Only to a Degree. - Peizhong Ju; Xiaojun Lin 001; Jia Liu 002 (NeurIPS, 2020)

Adaptive Multi-Hierarchical signSGD for Communication-Efficient Distributed Optimization. - Haibo Yang 001; Xin Zhang 054; Minghong Fang; Jia Liu 002 (SPAWC, 2020)

Influence Function based Data Poisoning Attacks to Top-N Recommender Systems. - Minghong Fang; Neil Zhenqiang Gong; Jia Liu 002 (WWW, 2020)

Randomized Bregman Coordinate Descent Methods for Non-Lipschitz Optimization. - Tianxiang Gao; Songtao Lu; Jia Liu 002; Chris Chu (CoRR, 2020)

Overfitting Can Be Harmless for Basis Pursuit: Only to a Degree. - Peizhong Ju; Xiaojun Lin 001; Jia Liu 002 (CoRR, 2020)

Multi-Armed Bandits with Local Differential Privacy. - Wenbo Ren; Xingyu Zhou 001; Jia Liu 002; Ness B. Shroff (CoRR, 2020)

Combinatorial Sleeping Bandits With Fairness Constraints. - Fengjiao Li; Jia Liu 002; Bo Ji 001 (IEEE Trans. Netw. Sci. Eng., 2020)

On Logarithmic Regret for Bandits with Knapsacks. - Wenbo Ren; Jia Liu 002; Ness B. Shroff (CISS, 2021)

On the Convergence of Randomized Bregman Coordinate Descent for Non-Lipschitz Composite Problems. - Tianxiang Gao; Songtao Lu; Jia Liu 002; Chris Chu (ICASSP, 2021)

Achieving Linear Speedup with Partial Worker Participation in Non-IID Federated Learning. - Haibo Yang 001; Minghong Fang; Jia Liu 002 (ICLR, 2021)

Incentivized Bandit Learning with Self-Reinforcing User Preferences. - Tianchen Zhou; Jia Liu 002; Chaosheng Dong; Jingyuan Deng (ICML, 2021)

A Sum-of-Ratios Multi-Dimensional-Knapsack Decomposition for DNN Resource Scheduling. - Menglu Yu; Chuan Wu 001; Bo Ji 001; Jia Liu 002 (INFOCOM, 2021)

Low Sample and Communication Complexities in Decentralized Learning: A Triple Hybrid Approach. - Xin Zhang 054; Jia Liu 002; Zhengyuan Zhu; Elizabeth Serena Bentley (INFOCOM, 2021)

Federated Learning with Fair Worker Selection: A Multi-Round Submodular Maximization Approach. - Fengjiao Li; Jia Liu 002; Bo Ji 001 (MASS, 2021)

ARA: A Wireless Living Lab Vision for Smart and Connected Rural Communities. - Hongwei Zhang 001; Yong Guan; Ahmed E. Kamal 001; Daji Qiao; Mai Zheng; Anish Arora; Ozdal Boyraz; Brian Cox; Thomas Daniels 001; Matthew J. Darr; Doug Jacobson; Ashfaq Khokhar 001; et al. (WiNTECH, 2021)

GT-STORM: Taming Sample, Communication, and Memory Complexities in Decentralized Non-Convex Learning. - Xin Zhang 054; Jia Liu 002; Zhengyuan Zhu; Elizabeth Serena Bentley (MobiHoc, 2021)

FLTrust: Byzantine-robust Federated Learning via Trust Bootstrapping. - Xiaoyu Cao; Minghong Fang; Jia Liu 002; Neil Zhenqiang Gong (NDSS, 2021)

STEM: A Stochastic Two-Sided Momentum Algorithm Achieving Near-Optimal Sample and Communication Complexities for Federated Learning. - Prashant Khanduri; Pranay Sharma; Haibo Yang 001; Mingyi Hong 001; Jia Liu 002; Ketan Rajawat; Pramod K. Varshney (NeurIPS, 2021)

Sample Complexity Bounds for Active Ranking from Multi-wise Comparisons. - Wenbo Ren; Jia Liu 002; Ness B. Shroff (NeurIPS, 2021)

Taming Communication and Sample Complexities in Decentralized Policy Evaluation for Cooperative Multi-Agent Reinforcement Learning. - Xin Zhang 054; Zhuqing Liu; Jia Liu 002; Zhengyuan Zhu; Songtao Lu (NeurIPS, 2021)

CFedAvg: Achieving Efficient Communication and Fast Convergence in Non-IID Federated Learning. - Haibo Yang 001; Jia Liu 002; Elizabeth S. Bentley (WiOpt, 2021)

Data Poisoning Attacks and Defenses to Crowdsourcing Systems. - Minghong Fang; Minghao Sun; Qi Li 012; Neil Zhenqiang Gong; Jin Tian 001; Jia Liu 002 (WWW, 2021)

Achieving Information Freshness With Selfish and Rational Users in Mobile Crowd-Learning. - Bin Li 014; Jia Liu 002 (IEEE J. Sel. Areas Commun., 2021)

Low-Overhead Wireless Uplink Scheduling for Large-Scale Internet-of-Things. - Bin Li 014; Jia Liu 002; Bo Ji 001 (IEEE Trans. Mob. Comput., 2021)

AFLGuard: Byzantine-robust Asynchronous Federated Learning. - Minghong Fang; Jia Liu 002; Neil Zhenqiang Gong; Elizabeth S. Bentley (ACSAC, 2022)

Leveraging Synergies Between AI and Networking to Build Next Generation Edge Networks. - Sen Lin 001; Ming Shi 003; Anish Arora; Raef Bassily; Elisa Bertino; Constantine Caramanis; Kaushik R. Chowdhury; Eylem Ekici; Atilla Eryilmaz; Stratis Ioannidis; Nan Jiang 008; Gauri Joshi; et al. (CIC, 2022)

A global convergence theory for deep ReLU implicit networks via over-parameterization. - Tianxiang Gao; Hailiang Liu; Jia Liu 002; Hridesh Rajan; Hongyang Gao (ICLR, 2022)

Finite-Time Convergence and Sample Complexity of Multi-Agent Actor-Critic Reinforcement Learning with Average Reward. - Hairi; Jia Liu 002; Songtao Lu (ICLR, 2022)

Decentralized Learning for Overparameterized Problems: A Multi-Agent Kernel Approximation Approach. - Prashant Khanduri; Haibo Yang 001; Mingyi Hong 001; Jia Liu 002; Hoi-To Wai; Sijia Liu 001 (ICLR, 2022)

Bandit Learning with Joint Effect of Incentivized Sampling, Delayed Sampling Feedback, and Self-Reinforcing User Preferences. - Tianchen Zhou; Jia Liu 002; Chaosheng Dong; Yi Sun (ICLR, 2022)

A Multi-objective / Multi-task Learning Framework Induced by Pareto Stationarity. - Michinari Momma; Chaosheng Dong; Jia Liu 002 (ICML, 2022)

Anarchic Federated Learning. - Haibo Yang 001; Xin Zhang 054; Prashant Khanduri; Jia Liu 002 (ICML, 2022)

GADGET: Online Resource Optimization for Scheduling Ring-All-Reduce Learning Jobs. - Menglu Yu; Ye Tian; Bo Ji 001; Chuan Wu 001; Hridesh Rajan; Jia Liu 002 (INFOCOM, 2022)

Over-the-Air Federated Learning with Joint Adaptive Computation and Power Control. - Haibo Yang 001; Peiwen Qiu; Jia Liu 002; Aylin Yener (ISIT, 2022)

INTERACT: achieving low sample and communication complexities in decentralized bilevel learning over networks. - Zhuqing Liu; Xin Zhang 054; Prashant Khanduri; Songtao Lu; Jia Liu 002 (MobiHoc, 2022)

SYNTHESIS: a semi-asynchronous path-integrated stochastic gradient method for distributed learning in computing clusters. - Zhuqing Liu; Xin Zhang 054; Jia Liu 002 (MobiHoc, 2022)

On scheduling ring-all-reduce learning jobs in multi-tenant GPU clusters with communication contention. - Menglu Yu; Bo Ji 001; Hridesh Rajan; Jia Liu 002 (MobiHoc, 2022)

NET-FLEET: achieving linear convergence speedup for fully decentralized federated learning with heterogeneous data. - Xin Zhang 054; Minghong Fang; Zhuqing Liu; Haibo Yang 001; Jia Liu 002; Zhengyuan Zhu (MobiHoc, 2022)

A Stochastic Linearized Augmented Lagrangian Method for Decentralized Bilevel Optimization. - Songtao Lu; Siliang Zeng; Xiaodong Cui; Mark S. Squillante; Lior Horesh; Brian Kingsbury; Jia Liu 002; Mingyi Hong 001 (NeurIPS, 2022)

SAGDA: Achieving $ mathcal{O}( epsilon^{-2})$ Communication Complexity in Federated Min-Max Learning. - Haibo Yang 001; Zhuqing Liu; Xin Zhang 054; Jia Liu 002 (NeurIPS, 2022)

Taming Fat-Tailed ("Heavier-Tailed" with Potentially Infinite Variance) Noise in Federated Learning. - Haibo Yang 001; Peiwen Qiu; Jia Liu 002 (NeurIPS, 2022)

FairRoad: Achieving Fairness for Recommender Systems with Optimized Antidote Data. - Minghong Fang; Jia Liu 002; Michinari Momma; Yi Sun (SACMAT, 2022)

CHARLES: Channel-Quality-Adaptive Over-the-Air Federated Learning over Wireless Networks. - Jiayu Mao; Haibo Yang 001; Peiwen Qiu; Jia Liu 002; Aylin Yener (SPAWC, 2022)

SAGDA: Achieving O(ε-2) Communication Complexity in Federated Min-Max Learning. - Haibo Yang 001; Zhuqing Liu; Xin Zhang 054; Jia Liu 002 (CoRR, 2022)

Distributed Traffic Flow Consolidation for Power Efficiency of Large-Scale Data Center Network. - Kuangyu Zheng; Xiaorui Wang; Jia Liu 002 (IEEE Trans. Cloud Comput., 2022)

Toward Efficient Online Scheduling for Distributed Machine Learning Systems. - Menglu Yu; Jia Liu 002; Chuan Wu 001; Bo Ji 001; Elizabeth S. Bentley (IEEE Trans. Netw. Sci. Eng., 2022)

An RC-Network Approach for HVAC Precooling Optimization in Buildings. - Hongsen Shi; Jia Liu 002; Qian Chen 026 (IEEE Trans. Sustain. Comput., 2022)

Linearly Constrained Bilevel Optimization: A Smoothed Implicit Gradient Approach. - Prashant Khanduri; Ioannis C. Tsaknakis; Yihua Zhang; Jia Liu 002; Sijia Liu 001; Jiawei Zhang 007; Mingyi Hong 001 (ICML, 2023)

Prometheus: Taming Sample and Communication Complexities in Constrained Decentralized Stochastic Bilevel Learning. - Zhuqing Liu; Xin Zhang 054; Prashant Khanduri; Songtao Lu; Jia Liu 002 (ICML, 2023)

DIAMOND: Taming Sample and Communication Complexities in Decentralized Bilevel Optimization. - Peiwen Qiu; Yining Li; Zhuqing Liu; Prashant Khanduri; Jia Liu 002; Ness B. Shroff; Elizabeth Serena Bentley; Kurt A. Turck (INFOCOM, 2023)

PRECISION: Decentralized Constrained Min-Max Learning with Low Communication and Sample Complexities. - Zhuqing Liu; Xin Zhang 054; Songtao Lu; Jia Liu 002 (MobiHoc, 2023)

Federated Multi-Objective Learning. - Haibo Yang 001; Zhuqing Liu; Jia Liu 002; Chaosheng Dong; Michinari Momma (NeurIPS, 2023)

Bandit Learning to Rank with Position-Based Click Models: Personalized and Equal Treatments. - Tianchen Zhou; Jia Liu 002; Yang Jiao; Chaosheng Dong; Yetian Chen; Yan Gao 029; Yi Sun (CoRR, 2023)

Guest Editorial: Interplay Between Machine Learning and Networking Systems. - Xiaowen Chu 001; Shadi Ibrahim; Jia Liu 002; Shiqiang Wang; Chuan Wu 001; Rongfei Zeng (IEEE Netw., 2023)

Sample and Communication Efficient Fully Decentralized MARL Policy Evaluation via a New Approach: Local TD Update. - Hairi; Zifan Zhang; Jia Liu 002 (AAMAS, 2024)

Byzantine-Robust Decentralized Federated Learning. - Minghong Fang; Zifan Zhang; Hairi; Prashant Khanduri; Jia Liu 002; Songtao Lu; Yuchen Liu 001; Neil Gong 001 (CCS, 2024)

PILOT: An $ mathcal{O}(1/K)$-Convergent Approach for Policy Evaluation with Nonlinear Function Approximation. - Zhuqing Liu; Xin Zhang 054; Jia Liu 002; Zhengyuan Zhu; Songtao Lu (ICLR, 2024)

Understanding Server-Assisted Federated Learning in the Presence of Incomplete Client Participation. - Haibo Yang 001; Peiwen Qiu; Prashant Khanduri; Minghong Fang; Jia Liu 002 (ICML, 2024)

Finite-Time Convergence and Sample Complexity of Actor-Critic Multi-Objective Reinforcement Learning. - Tianchen Zhou; Hairi; Haibo Yang 001; Jia Liu 002; Tian Tong; Fan Yang 084; Michinari Momma; Yan Gao 029 (ICML, 2024)

Can We Theoretically Quantify the Impacts of Local Updates on the Generalization Performance of Federated Learning? - Peizhong Ju; Haibo Yang 001; Jia Liu 002; Yingbin Liang; Ness B. Shroff (MobiHoc, 2024)

On the Hardness of Decentralized Multi-Agent Policy Evaluation Under Byzantine Attacks. - Hairi; Minghong Fang; Zifan Zhang; Alvaro Velasquez; Jia Liu 002 (WiOpt, 2024)

Drift to Remember. - Jin Du; Xinhe Zhang; Hao Shen; Xun Xian; Ganghua Wang; Jiawei Zhang 007; Yuhong Yang 002; Na Li 002; Jia Liu 002; Jie Ding 002 (CoRR, 2024)

DUET: Decentralized Bilevel Optimization without Lower-Level Strong Convexity. - Zhen Qin; Zhuqing Liu; Songtao Lu; Yingbin Liang; Jia Liu 002 (ICLR, 2025)

Prediction-Assisted Online Distributed Deep Learning Workload Scheduling in GPU Clusters. - Ziyue Luo; Jia Liu 002; Myungjin Lee; Ness B. Shroff (INFOCOM, 2025)

STIMULUS: Achieving Fast Convergence and Low Sample Complexity in Stochastic Multi-Objective Learning. - Zhuqing Liu; Chaosheng Dong; Michinari Momma; Simone Shao; Shaoyuan Xu; Yan Gao 029; Haibo Yang 001; Jia Liu 002 (UAI, 2025)

Divide and Orthogonalize: Efficient Continual Learning with Local Model Space Projection. - Jin Shang; Simone Shao; Tian Tong; Fan Yang 084; Yetian Chen; Yang Jiao; Jia Liu 002; Yan Gao 029 (UAI, 2025)

Byzantine-Robust Federated Learning over Ring-All-Reduce Distributed Computing. - Minghong Fang; Zhuqing Liu; Xuecen Zhao; Jia Liu 002 (WWW (Companion Volume), 2025)

PCL: Prompt-based Continual Learning for User Modeling in Recommender Systems. - Mingdai Yang; Fan Yang 084; Yanhui Guo; Shaoyuan Xu; Tianchen Zhou; Yetian Chen; Simone Shao; Jia Liu 002; Yan Gao 029 (WWW (Companion Volume), 2025)

Finite-Time Global Optimality Convergence in Deep Neural Actor-Critic Methods for Decentralized Multi-Agent Reinforcement Learning. - Zhiyao Zhang; Myeung Suk Oh; Hairi; Ziyue Luo; Alvaro Velasquez; Jia Liu 002 (CoRR, 2025)

Enabling Pareto-Stationarity Exploration in Multi-Objective Reinforcement Learning: A Multi-Objective Weighted-Chebyshev Actor-Critic Approach. - Hairi; Jiao Yang; Tianchen Zhou; Haibo Yang 001; Chaosheng Dong; Fan Yang 084; Michinari Momma; Yan Gao 029; Jia Liu 002 (CoRR, 2025)

Consensus-based Decentralized Multi-agent Reinforcement Learning for Random Access Network Optimization. - Myeung Suk Oh; Zhiyao Zhang; FNU Hairi; Alvaro Velasquez; Jia Liu 002 (CoRR, 2025)