Semantic-Oriented Ubiquitous Learning Object Management System SULOMS. - Lili Su; Shenggang Yang; Yushun Li; Xiaochun Cheng; Ronghuai Huang (COMPSAC, 2008)

FPGA-Accelerated Molecular Dynamics Simulations System. - He Guo 001; Lili Su; Yuxin Wang 001; Zhu Long (ScalCom-EmbeddedCom, 2009)

Simulation analysis of error correction method of headlamp detection based on driving direction. - Hongying Shan; Lili Su; Songyan Pan; Shubin Ge; Libin Zhang (WCNIS, 2010)

Computing Similarity Distances Between Rankings. - Lili Su; Farzad Farnoud; Olgica Milenkovic (CoRR, 2013)

Application Performance Monitoring and Analyzing Based on Bayesian Network. - Chao Wang 054; Lili Su; Xue Zhao 001; Ying Zhang 015 (IEEE WISA, 2014)

Social Advertisability Analysis on Twitter. - Ying Zhang 015; Xue Zhao 001; Chao Wang 054; Ya Wang; Lili Su; Xiaojie Yuan (IEEE WISA, 2014)

Similarity distances between permutations. - Lili Su; Farzad Farnoud; Olgica Milenkovic (ISIT, 2014)

Synchronizing rankings via interactive communication. - Lili Su; Olgica Milenkovic (ISIT, 2014)

Multi-Label Emotion Tagging for Online News by Supervised Topic Model. - Ying Zhang 015; Lili Su; Zhifan Yang; Xue Zhao 001; Xiaojie Yuan (APWeb, 2015)

Byzantine Multi-Agent Optimization: Part I. - Lili Su; Nitin H. Vaidya (CoRR, 2015)

Byzantine Multi-Agent Optimization: Part II. - Lili Su; Nitin H. Vaidya (CoRR, 2015)

Fault-Tolerant Multi-Agent Optimization: Part III. - Lili Su; Nitin H. Vaidya (CoRR, 2015)

Fault-Tolerant Distributed Optimization (Part IV): Constrained Optimization with Arbitrary Directed Networks. - Lili Su; Nitin H. Vaidya (CoRR, 2015)

Multi-agent optimization in the presence of Byzantine adversaries: Fundamental limits. - Lili Su; Nitin H. Vaidya (ACC, 2016)

Fault-Tolerant Multi-Agent Optimization: Optimal Iterative Distributed Algorithms. - Lili Su; Nitin H. Vaidya (PODC, 2016)

Asynchronous Non-Bayesian Learning in the Presence of Crash Failures. - Lili Su; Nitin H. Vaidya (SSS, 2016)

Robust Multi-agent Optimization: Coping with Byzantine Agents with Input Redundancy. - Lili Su; Nitin H. Vaidya (SSS, 2016)

Non-Bayesian Learning in the Presence of Byzantine Agents. - Lili Su; Nitin H. Vaidya (DISC, 2016)

Asynchronous Distributed Hypothesis Testing in the Presence of Crash Failures. - Lili Su; Nitin H. Vaidya (CoRR, 2016)

Robust Multi-Agent Optimization: Coping with Packet-Dropping Link Failures. - Lili Su; Nitin H. Vaidya (CoRR, 2016)

DISC 2016 Review. - Lili Su (SIGACT News, 2016)

Ant-Inspired Dynamic Task Allocation via Gossiping. - Hsin-Hao Su; Lili Su; Anna R. Dornhaus; Nancy A. Lynch (SSS, 2017)

Computing similarity distances between rankings. - Farzad Farnoud Hassanzadeh; Olgica Milenkovic; Gregory J. Puleo; Lili Su (Discret. Appl. Math., 2017)

Reaching approximate Byzantine consensus with multi-hop communication. - Lili Su; Nitin H. Vaidya (Inf. Comput., 2017)

Distributed Statistical Machine Learning in Adversarial Settings: Byzantine Gradient Descent. - Yudong Chen 001; Lili Su; Jiaming Xu 002 (Proc. ACM Meas. Anal. Comput. Syst., 2017)

Defending distributed systems against adversarial attacks: consensus, consensus-based learning, and statistical learning - Lili Su (2017)

On the Convergence Rate of Average Consensus and Distributed optimization over Unreliable Networks. - Lili Su (ACSSC, 2018)

Collaboratively Learning the Best Option, Using Bounded Memory. - Lili Su; Martin Zubeldia; Nancy A. Lynch (CoRR, 2018)

Securing Distributed Machine Learning in High Dimensions. - Lili Su; Jiaming Xu 002 (CoRR, 2018)

Distributed Learning over Time-Varying Graphs with Adversarial Agents. - Pooja Vyavahare; Lili Su; Nitin H. Vaidya (FUSION, 2019)

On Learning Over-parameterized Neural Networks: A Functional Approximation Perspective. - Lili Su; Pengkun Yang (NeurIPS, 2019)

Distributed Learning with Adversarial Agents Under Relaxed Network Condition. - Pooja Vyavahare; Lili Su; Nitin H. Vaidya (CoRR, 2019)

On Learning Over-parameterized Neural Networks: A Functional Approximation Prospective. - Lili Su; Pengkun Yang (CoRR, 2019)

Defending non-Bayesian learning against adversarial attacks. - Lili Su; Nitin H. Vaidya (Distributed Comput., 2019)

Spike-Based Winner-Take-All Computation: Fundamental Limits and Order-Optimal Circuits. - Lili Su; Chia-Jung Chang; Nancy A. Lynch (Neural Comput., 2019)

Securing Distributed Gradient Descent in High Dimensional Statistical Learning. - Lili Su; Jiaming Xu 002 (Proc. ACM Meas. Anal. Comput. Syst., 2019)

Collaboratively Learning the Best Option on Graphs, Using Bounded Local Memory. - Lili Su; Martin Zubeldia; Nancy A. Lynch (Proc. ACM Meas. Anal. Comput. Syst., 2019)

Defending Distributed Systems Against Adversarial Attacks: Consensus, Consensusbased Learning, and Statistical Learning. - Lili Su (SIGMETRICS Perform. Evaluation Rev., 2019)

The Analysis of Higher Mathematics Teaching Strategy Based on the Innovative Teaching Mode. - Xuhui Fan 003; Wei Li; Zhimin Wang; Yiyue Sun; Lili Su (IMIS, 2020)

Teaching Evaluation Index Based on Analytic Hierarchy Process. - Qiong Li; Yanyan Zhao; Jiangtao Li; Lili Su (INCoS, 2020)

Adaptive Active Vehicle Interior Noise Control Algorithm Based on Nonlinear Signal Reconstruction. - Xiaolan Wang 002; Tongzhou Wang 003; Lili Su; Yansong Wang; Dongpo Yang; Chao Yang; Ningning Liu (Circuits Syst. Signal Process., 2020)

A new safe lane-change trajectory model and collision avoidance control method for automatic driving vehicles. - Tao Peng; Lili Su; Ronghui Zhang; Zhiwei Guan; Honglin Zhao; Zhijun Tony Qiu; Changfu Zong; Hongguo Xu (Expert Syst. Appl., 2020)

An improved evolution fruit fly optimization algorithm and its application. - Xuan Yang; Weide Li; Lili Su; Yaling Wang; Ailing Yang (Neural Comput. Appl., 2020)

Finite-Time Guarantees for Byzantine-Resilient Distributed State Estimation With Noisy Measurements. - Lili Su; Shahin Shahrampour (IEEE Trans. Autom. Control., 2020)

Lack of Quorum Sensing Leads to Failure of Consensus in Temnothorax Ant Emigration. - Jiajia Zhao; Lili Su; Nancy A. Lynch (SSS, 2021)

The Power of Random Symmetry-Breaking in Nakamoto Consensus. - Lili Su; Quanquan C. Liu; Neha Narula (DISC, 2021)

Achieving Statistical Optimality of Federated Learning: Beyond Stationary Points. - Lili Su; Jiaming Xu 002; Pengkun Yang (CoRR, 2021)

Byzantine-Resilient Multiagent Optimization. - Lili Su; Nitin H. Vaidya (IEEE Trans. Autom. Control., 2021)

β-Stochastic Sign SGD: A Byzantine Resilient and Differentially Private Gradient Compressor for Federated Learning. - Ming Xiang; Lili Su (CoRR, 2022)

Service Function Chain Scheduling Method for Power Wide Coverage 5G Multi-link Converged Networks. - Qinghai Ou; Yanru Wang; Hong Zhu; Wendi Wang 004; Lili Su; Ying Wang 002 (BMSB, 2023)

Multi-level Intelligent Collaborative Computing Mechanism Based on DDQN for Smart Highways. - Sujie Shao; Lili Su; Ruijun Chai; Shaoyong Guo; Siya Xu; Juntao Zheng (BMSB, 2023)

Towards Bias Correction of FedAvg over Nonuniform and Time-Varying Communications. - Ming Xiang; Stratis Ioannidis; Edmund Yeh; Carlee Joe-Wong; Lili Su (CDC, 2023)

Teaching Method of Advanced Mathematics Combining PAD Classroom with ADDIE Model. - Yanyan Zhao; Qiong Li; Xuhui Fan 003; Lili Su; Jingtao Li; Xiaokang Liu (EIDWT, 2023)

Poster Abstract: Fair Training of Multiple Federated Learning Models on Resource Constrained Network Devices. - Marie Siew; Shoba Arunasalam; Yichen Ruan; Ziwei Zhu; Lili Su; Stratis Ioannidis; Edmund Yeh; Carlee Joe-Wong (IPSN, 2023)

Privacy-Preserving and Uncertainty-Aware Federated Trajectory Prediction for Connected Autonomous Vehicles. - Muzi Peng; Jiangwei Wang; Dongjin Song; Fei Miao; Lili Su (IROS, 2023)

Cache-Enabled Federated Learning Systems. - Yuezhou Liu; Lili Su; Carlee Joe-Wong; Stratis Ioannidis; Edmund Yeh; Marie Siew (MobiHoc, 2023)

Nonlocalization of singular potentials in quantum dynamics. - Sihong Shao; Lili Su (CoRR, 2023)

Federated Learning in the Presence of Adversarial Client Unavailability. - Lili Su; Jiaming Xu 002; Pengkun Yang (CoRR, 2023)

Fast and Robust State Estimation and Tracking via Hierarchical Learning. - Connor Mclaughlin; Matthew Ding 001; Deniz Edogmus; Lili Su (CoRR, 2023)

Network Fault-tolerant and Byzantine-resilient Social Learning via Collaborative Hierarchical Non-Bayesian Learning. - Connor Mclaughlin; Matthew Ding 001; Deniz Edogmus; Lili Su (CoRR, 2023)

A Non-parametric View of FedAvg and FedProx:Beyond Stationary Points. - Lili Su; Jiaming Xu 002; Pengkun Yang (J. Mach. Learn. Res., 2023)

Multi task dynamic edge-end computing collaboration for urban Internet of Vehicles. - Sujie Shao; Lili Su; Qinghang Zhang; Shuang Wu; Shaoyong Guo; Feng Qi 004 (Comput. Networks, 2023)

Multi-Agent Cooperative Game Based Task Computing Mechanism for UAV-Assisted 6G NTN. - Sujie Shao; Lili Su; Shaoyong Guo; Peng Yu 001; Xuesong Qiu 001 (Mob. Networks Appl., 2023)

Experimental Design Networks: A Paradigm for Serving Heterogeneous Learners Under Networking Constraints. - Yuanyuan Li; Yuezhou Liu; Lili Su; Edmund Yeh; Stratis Ioannidis (IEEE/ACM Trans. Netw., 2023)

Byzantine-Resilient Collaborative Hierarchical Non-Bayesian Learning. - Connor Mclaughlin; Matthew Ding 001; Deniz Erdogmus; Lili Su (IEEECONF, 2024)

Investigation of Location Problem in Logistics Centers Using ADMM Algorithm. - Lili Su; Qiong Li; Xiaolong Ma; Xuan Wang (CISIS, 2024)

Non-transferable Pruning. - Ruyi Ding; Lili Su; Aidong Adam Ding; Yunsi Fei (ECCV (86), 2024)

An Evaluation Model of the Effectiveness of College Club Activities Based on Grey Relational Analysis. - Qiong Li; Lili Su; Yanyan Zhao; Lixing Li; Xuan Wang (IMIS, 2024)

Distributed Experimental Design Networks. - Yuanyuan Li; Lili Su; Carlee Joe-Wong; Edmund Yeh; Stratis Ioannidis (INFOCOM, 2024)

Personalized Federated Learning via Feature Distribution Adaptation. - Connor Mclaughlin; Lili Su (NeurIPS, 2024)

Efficient Federated Learning against Heterogeneous and Non-stationary Client Unavailability. - Ming Xiang; Stratis Ioannidis; Edmund Yeh; Carlee Joe-Wong; Lili Su (NeurIPS, 2024)

RSBuilding: Towards General Remote Sensing Image Building Extraction and Change Detection with Foundation Model. - Mingze Wang; Keyan Chen; Lili Su; Cilin Yan; Sheng Xu 007; Haotian Zhang; Pengcheng Yuan; Xiaolong Jiang; Baochang Zhang 001 (CoRR, 2024)

Fair Concurrent Training of Multiple Models in Federated Learning. - Marie Siew; Haoran Zhang; Jong-Ik Park; Yuezhou Liu; Yichen Ruan; Lili Su; Stratis Ioannidis; Edmund Yeh; Carlee Joe-Wong (CoRR, 2024)

Collaborative Learning with Shared Linear Representations: Statistical Rates and Optimal Algorithms. - Xiaochun Niu; Lili Su; Jiaming Xu 002; Pengkun Yang (CoRR, 2024)

Reactive Multi-Robot Navigation in Outdoor Environments Through Uncertainty-Aware Active Learning of Human Preference Landscape. - Chao Huang; Wenshuo Zang; Carlo Pinciroli; Zhi Jane Li; Taposh Banerjee; Lili Su; Rui Liu (CoRR, 2024)

Building Real-time Awareness of Out-of-distribution in Trajectory Prediction for Autonomous Vehicles. - Tongfei Guo; Taposh Banerjee; Rui Liu; Lili Su (CoRR, 2024)

Data-efficient Trajectory Prediction via Coreset Selection. - Ruining Yang; Lili Su (CoRR, 2024)

RSBuilding: Toward General Remote Sensing Image Building Extraction and Change Detection With Foundation Model. - Mingze Wang; Lili Su; Cilin Yan; Sheng Xu 007; Pengcheng Yuan; Xiaolong Jiang; Baochang Zhang 001 (IEEE Trans. Geosci. Remote. Sens., 2024)

Towards Safe Autonomy in Hybrid Traffic: Detecting Unpredictable Abnormal Behaviors of Human Drivers via Information Sharing. - Jiangwei Wang; Lili Su; Songyang Han; Dongjin Song; Fei Miao (ACM Trans. Cyber Phys. Syst., 2024)

Global Convergence of Federated Learning for Mixed Regression. - Lili Su; Jiaming Xu 002; Pengkun Yang (IEEE Trans. Inf. Theory, 2024)

Probe-Me-Not: Protecting Pre-trained Encoders from Malicious Probing. - Ruyi Ding; Tong Zhou 002; Lili Su; Aidong Adam Ding; Xiaolin Xu 001; Yunsi Fei (NDSS, 2025)

Latency-optimized multi-task collaborative computing mechanism based on NOMA-D2D for AIoT. - Sujie Shao; Lili Su; Shaoyong Guo; Siya Xu; Xuesong Qiu 001 (Comput. Commun., 2025)

A visual tracking algorithm based on context constraint and aberration suppression. - Yinqiang Su; Lili Su; Fang Xu; Hui Zhao (Knowl. Based Syst., 2025)

On the Convergence Rates of Federated Q-Learning across Heterogeneous Environments. - Muxing Wang; Pengkun Yang; Lili Su (Trans. Mach. Learn. Res., 2025)

Empowering Federated Learning With Implicit Gossiping: Mitigating Connection Unreliability Amidst Unknown and Arbitrary Dynamics. - Ming Xiang; Stratis Ioannidis; Edmund Yeh; Carlee Joe-Wong; Lili Su (IEEE Trans. Signal Process., 2025)

Introduction to the Special Issue on Performance Evaluation of Federated Learning Systems Part 1. - Carlee Joe-Wong; Lili Su (ACM Trans. Model. Perform. Evaluation Comput. Syst., 2025)

Trajectory Prediction Meets Large Language Models: A Survey. - Yi Xu; Ruining Yang; Yitian Zhang; Yizhou Wang; Jianglin Lu; Mingyuan Zhang; Lili Su; Yun Fu (CoRR, 2025)

Introduction to the Special Issue on Performance Evaluation of Federated Learning Systems Part 2. - Carlee Joe-Wong; Lili Su (ACM Trans. Model. Perform. Evaluation Comput. Syst., 2025)