FISF: Better User Experience using Smaller Bandwidth for Panoramic Virtual Reality Video. - Lun Wang 001; Damai Dai; Jie Jiang 008; Tong Yang 003; Xiaoke Jiang; Zekun Cai; Yang Li; Xiaoming Li 001 (CoRR, 2017)

Fine-Grained Probability Counting: Refined LogLog Algorithm. - Lun Wang 001; Zekun Cai; Hao Wang 005; Jie Jiang 008; Tong Yang 003; Bin Cui 001; Xiaoming Li 001 (BigComp, 2018)

Empowering Sketches with Machine Learning for Network Measurements. - Tong Yang 003; Lun Wang 001; Yulong Shen 001; Muhammad Shahzad 001; Qun Huang 001; Xiaohong Jiang 001; Kun Tan; Xiaoming Li 001 (NetAI@SIGCOMM, 2018)

A Generic Technique for Sketches to Adapt to Different Counting Ranges. - Tong Yang 003; Jiaqi Xu; Xilai Liu; Peng Liu 047; Lun Wang 001; Jun Bi; Xiaoming Li 001 (INFOCOM, 2019)

Towards Practical Differentially Private Convex Optimization. - Roger Iyengar; Joseph P. Near; Dawn Song; Om Thakkar 001; Abhradeep Thakurta; Lun Wang 001 (IEEE Symposium on Security and Privacy, 2019)

Data Capsule: A New Paradigm for Automatic Compliance with Data Privacy Regulations. - Lun Wang 001; Joseph P. Near; Neel Somani; Peng Gao 008; Andrew Low; David Dao; Dawn Song (Poly/DMAH@VLDB, 2019)

TABOR: A Highly Accurate Approach to Inspecting and Restoring Trojan Backdoors in AI Systems. - Wenbo Guo 002; Lun Wang 001; Xinyu Xing 001; Min Du 003; Dawn Song (CoRR, 2019)

CHURP: Dynamic-Committee Proactive Secret Sharing. - Sai Krishna Deepak Maram; Fan Zhang 022; Lun Wang 001; Andrew Low; Yupeng Zhang 001; Ari Juels; Dawn Song (IACR Cryptol. ePrint Arch., 2019)

Duet: an expressive higher-order language and linear type system for statically enforcing differential privacy. - Joseph P. Near; David Darais; Chike Abuah; Tim Stevens; Pranav Gaddamadugu; Lun Wang 001; Neel Somani; Mu Zhang 001; Nikhil Sharma; Alex Shan; Dawn Song (Proc. ACM Program. Lang., 2019)

Fine-grained probability counting for cardinality estimation of data streams. - Lun Wang 001; Tong Yang 003; Hao Wang 005; Jie Jiang 008; Zekun Cai; Bin Cui 001; Xiaoming Li 001 (World Wide Web, 2019)

Towards Inspecting and Eliminating Trojan Backdoors in Deep Neural Networks. - Wenbo Guo 002; Lun Wang 001; Yan Xu; Xinyu Xing 001; Min Du 003; Dawn Song (ICDM, 2020)

Towards practical differentially private causal graph discovery. - Lun Wang 001; Qi Pang; Dawn Song (NeurIPS, 2020)

Private Distributed Mean Estimation. - Lun Wang 001; Ruoxi Jia 001 (CoRR, 2020)

F2ED-Learning: Good Fences Make Good Neighbors. - Lun Wang 001; Qi Pang; Shuai Wang 011; Dawn Song (CoRR, 2020)

PrivFramework: A System for Configurable and Automated Privacy Policy Compliance. - Usmann Khan; Lun Wang 001; Jithendaraa Subramanian; Joseph P. Near; Dawn Song (CoRR, 2020)

BACKDOORL: Backdoor Attack against Competitive Reinforcement Learning. - Lun Wang 001; Zaynah Javed; Xian Wu 007; Wenbo Guo 002; Xinyu Xing 001; Dawn Song (IJCAI, 2021)

Differentially Private Frequency Moments Estimation with Polylogarithmic Space. - Lun Wang 001; Dawn Song (CoRR, 2021)

FED-χ2: Privacy Preserving Federated Correlation Test. - Lun Wang 001; Qi Pang; Shuai Wang 011; Dawn Song (CoRR, 2021)

DPlis: Boosting Utility of Differentially Private Deep Learning via Randomized Smoothing. - Wenxiao Wang 002; Tianhao Wang 013; Lun Wang 001; Nanqing Luo; Pan Zhou; Dawn Song; Ruoxi Jia 001 (Proc. Priv. Enhancing Technol., 2021)

Differentially Private Fractional Frequency Moments Estimation with Polylogarithmic Space. - Lun Wang 001; Iosif Pinelis; Dawn Song (ICLR, 2022)

PrivGuard: Privacy Regulation Compliance Made Easier. - Lun Wang 001; Usmann Khan; Joseph P. Near; Qi Pang; Jithendaraa Subramanian; Neel Somani; Peng Gao 008; Andrew Low; Dawn Song (USENIX Security Symposium, 2022)

Byzantine-Robust Federated Learning with Optimal Statistical Rates and Privacy Guarantees. - Banghua Zhu; Lun Wang 001; Qi Pang; Shuai Wang 011; Jiantao Jiao; Dawn Song; Michael I. Jordan (CoRR, 2022)

SEAD Counter: Self-Adaptive Counters With Different Counting Ranges. - Xilai Liu; Yan Xu; Peng Liu 047; Tong Yang 003; Jiaqi Xu; Lun Wang 001; Gaogang Xie; Xiaoming Li 001; Steve Uhlig (IEEE/ACM Trans. Netw., 2022)

Towards Privacy-Preserving and Regulation-Compliant Data Analysis - Lun Wang 001 (2022)

Byzantine-Robust Federated Learning with Optimal Statistical Rates. - Banghua Zhu; Lun Wang 001; Qi Pang; Shuai Wang 011; Jiantao Jiao; Dawn Song; Michael I. Jordan (AISTATS, 2023)

Why Is Public Pretraining Necessary for Private Model Training? - Arun Ganesh; Mahdi Haghifam; Milad Nasr; Sewoong Oh; Thomas Steinke 002; Om Thakkar 001; Abhradeep Guha Thakurta; Lun Wang 001 (ICML, 2023)

Secure Federated Correlation Test and Entropy Estimation. - Qi Pang; Lun Wang 001; Shuai Wang 011; Wenting Zheng; Dawn Song (ICML, 2023)

PATROL: Provable Defense against Adversarial Policy in Two-player Games. - Wenbo Guo 002; Xian Wu 007; Lun Wang 001; Xinyu Xing 001; Dawn Song (USENIX Security Symposium, 2023)

Ratel: MPC-extensions for Smart Contracts. - Yunqi Li 002; Kyle Soska; Zhen Huang; Sylvain Bellemare; Mikerah Quintyne-Collins; Lun Wang 001; Xiaoyuan Liu; Dawn Song; Andrew Miller 001 (IACR Cryptol. ePrint Arch., 2023)

Noise Masking Attacks and Defenses for Pretrained Speech Models. - Matthew Jagielski; Om Thakkar 001; Lun Wang 001 (ICASSP, 2024)

Unintended Memorization in Large ASR Models, and How to Mitigate It. - Lun Wang 001; Om Thakkar 001; Rajiv Mathews (ICASSP, 2024)

Efficiently Train ASR Models that Memorize Less and Perform Better with Per-core Clipping. - Lun Wang 001; Om Thakkar 001; Zhong Meng; Nicole Rafidi; Rohit Prabhavalkar; Arun Narayanan (INTERSPEECH, 2024)

Differentially Private Parameter-Efficient Fine-tuning for Large ASR Models. - Hongbin Liu; Lun Wang 001; Om Thakkar 001; Abhradeep Thakurta; Arun Narayanan (CoRR, 2024)