RiskPatrol: A risk management system considering the integration risk management with business continuity processes. - Shi-Cho Cha 001; Pei-Wen Juo; Li-Ting Liu; Wei-Ning Chen (ISI, 2008)

Duplicate Work Reduction in Business Continuity and Risk Management Processes. - Shi-Cho Cha 001; Pei-Wen Juo; Li-Ting Liu; Wei-Ning Chen (Security Informatics, 2010)

Energy-Efficient Deterministic Adaptive Beamforming Algorithms for Distributed Sensor/Relay Networks. - Chun-Wei Li; Kuo-Ming Chen; Po-Chun Fu; Wei-Ning Chen; Che Lin (CoRR, 2015)

Partial data extraction via noisy histogram queries: Information theoretic bounds. - Wei-Ning Chen; I-Hsiang Wang (ISIT, 2017)

Dynamic Path Pruning in Symbolic Execution. - Ying-Shen Chen; Wei-Ning Chen; Che-Yu Wu; Hsu-Chun Hsiao; Shih-Kun Huang (DSC, 2018)

On the Fundamental Limits of Heterogeneous Distributed Detection: Price of Anonymity. - Wei-Ning Chen; Ho-Chun Chen; I-Hsiang Wang (ISIT, 2018)

On the Price of Source Anonymity in Heterogeneous Parametric Point Estimation. - Wei-Ning Chen; I-Hsiang Wang (ISIT, 2019)

Anonymous Heterogeneous Distributed Detection: Optimal Decision Rules, Error Exponents, and the Price of Anonymity. - Wei-Ning Chen; I-Hsiang Wang (IEEE Trans. Inf. Theory, 2019)

Fisher Information Under Local Differential Privacy. - Leighton Pate Barnes; Wei-Ning Chen; Ayfer Özgür (IEEE J. Sel. Areas Inf. Theory, 2020)

Breaking The Dimension Dependence in Sparse Distribution Estimation under Communication Constraints. - Wei-Ning Chen; Peter Kairouz; Ayfer Özgür (COLT, 2021)

Adaptive Group Testing on Networks with Community Structure. - Surin Ahn; Wei-Ning Chen; Ayfer Özgür (ISIT, 2021)

Differentially Private Federated Learning: An Information-Theoretic Perspective. - Shahab Asoodeh; Wei-Ning Chen; Flávio P. Calmon; Ayfer Özgür (ISIT, 2021)

Pointwise Bounds for Distribution Estimation under Communication Constraints. - Wei-Ning Chen; Peter Kairouz; Ayfer Özgür (NeurIPS, 2021)

Optimal Compression of Locally Differentially Private Mechanisms. - Abhin Shah; Wei-Ning Chen; Johannes Ballé; Peter Kairouz; Lucas Theis (AISTATS, 2022)

The Fundamental Price of Secure Aggregation in Differentially Private Federated Learning. - Wei-Ning Chen; Christopher A. Choquette-Choo; Peter Kairouz; Ananda Theertha Suresh (ICML, 2022)

The Poisson Binomial Mechanism for Unbiased Federated Learning with Secure Aggregation. - Wei-Ning Chen; Ayfer Özgür; Peter Kairouz (ICML, 2022)

Estimating Sparse Distributions Under Joint Communication and Privacy Constraints. - Surin Ahn; Wei-Ning Chen; Ayfer Özgür (ISIT, 2022)

The Poisson binomial mechanism for secure and private federated learning. - Wei-Ning Chen; Ayfer Özgür; Peter Kairouz (CoRR, 2022)

The communication cost of security and privacy in federated frequency estimation. - Wei-Ning Chen; Ayfer Özgür; Graham Cormode; Akash Bharadwaj (AISTATS, 2023)

Noisy Adaptive Group Testing for Community-Oriented Models. - Surin Ahn; Wei-Ning Chen; Ayfer Özgür (ISIT, 2023)

Privacy Amplification via Compression: Achieving the Optimal Privacy-Accuracy-Communication Trade-off in Distributed Mean Estimation. - Wei-Ning Chen; Dan Song; Ayfer Özgür; Peter Kairouz (NeurIPS, 2023)

Differentially Private Decoupled Graph Convolutions for Multigranular Topology Protection. - Eli Chien; Wei-Ning Chen; Chao Pan 003; Pan Li 005; Ayfer Özgür; Olgica Milenkovic (NeurIPS, 2023)

Exact Optimality of Communication-Privacy-Utility Tradeoffs in Distributed Mean Estimation. - Berivan Isik; Wei-Ning Chen; Ayfer Özgür; Tsachy Weissman; Albert No (NeurIPS, 2023)

Training generative models from privatized data. - Daria Reshetova; Wei-Ning Chen; Ayfer Özgür (CoRR, 2023)

Breaking the Communication-Privacy-Accuracy Trilemma. - Wei-Ning Chen; Peter Kairouz; Ayfer Özgür (IEEE Trans. Inf. Theory, 2023)

Adaptive Group Testing on Networks With Community Structure: The Stochastic Block Model. - Surin Ahn; Wei-Ning Chen; Ayfer Özgür (IEEE Trans. Inf. Theory, 2023)

Federated Experiment Design under Distributed Differential Privacy. - Wei-Ning Chen; Graham Cormode; Akash Bharadwaj; Peter Romov; Ayfer Özgür (AISTATS, 2024)

Over-the-Air Histogram Estimation. - Henrik Hellström; Jiwon Jeong; Wei-Ning Chen; Ayfer Özgür; Viktoria Fodor; Carlo Fischione (ICC, 2024)

Improved Communication-Privacy Trade-offs in L2 Mean Estimation under Streaming Differential Privacy. - Wei-Ning Chen; Berivan Isik; Peter Kairouz; Albert No; Sewoong Oh; Zheng Xu 002 (ICML, 2024)

Lq Lower Bounds on Distributed Estimation via Fisher Information. - Wei-Ning Chen; Ayfer Özgür (ISIT, 2024)

Universal Exact Compression of Differentially Private Mechanisms. - Yanxiao Liu 003; Wei-Ning Chen; Ayfer Özgür; Cheuk Ting Li (NeurIPS, 2024)

Lq Lower Bounds on Distributed Estimation via Fisher Information. - Wei-Ning Chen; Ayfer Özgür (CoRR, 2024)

Improved Communication-Privacy Trade-offs in L2 Mean Estimation under Streaming Differential Privacy. - Wei-Ning Chen; Berivan Isik; Peter Kairouz; Albert No; Sewoong Oh; Zheng Xu 002 (CoRR, 2024)

Randomization Techniques to Mitigate the Risk of Copyright Infringement. - Wei-Ning Chen; Peter Kairouz; Sewoong Oh; Zheng Xu 002 (CoRR, 2024)

Differentially Private Adaptation of Diffusion Models via Noisy Aggregated Embeddings. - Pura Peetathawatchai; Wei-Ning Chen; Berivan Isik; Sanmi Koyejo; Albert No (CoRR, 2024)

Training Generative Models From Privatized Data via Entropic Optimal Transport. - Daria Reshetova; Wei-Ning Chen; Ayfer Özgür (IEEE J. Sel. Areas Inf. Theory, 2024)

Leveraging Randomness in Model and Data Partitioning for Privacy Amplification. - Andy Dong; Wei-Ning Chen; Ayfer Özgür (CoRR, 2025)

Privacy Amplification in Differentially Private Zeroth-Order Optimization with Hidden States. - Eli Chien; Wei-Ning Chen; Pan Li 005 (CoRR, 2025)