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Synapse: a microservices architecture for heterogeneous-database web applications., , , , and . EuroSys, page 21:1-21:16. ACM, (2015)Certified Robustness to Adversarial Examples with Differential Privacy., , , , and . IEEE Symposium on Security and Privacy, page 656-672. IEEE, (2019)Security, Privacy, and Transparency Guarantees for Machine Learning Systems.. Columbia University, USA, (2019)Dispatch: secure, resilient mobile reporting., , , , , , , , and . SIGCOMM, page 459-460. ACM, (2013)DP-AdamBC: Your DP-Adam Is Actually DP-SGD (Unless You Apply Bias Correction)., , and . AAAI, page 15276-15283. AAAI Press, (2024)Sayer: Using Implicit Feedback to Optimize System Policies., , , , , , and . SoCC, page 273-288. ACM, (2021)Improving the Transparency of the Sharing Economy., , and . WWW (Companion Volume), page 1043-1051. ACM, (2017)GlueFL: Reconciling Client Sampling and Model Masking for Bandwidth Efficient Federated Learning., , , , , and . MLSys, mlsys.org, (2023)Adaptive Randomized Smoothing: Certifying Multi-Step Defences against Adversarial Examples., , , , and . CoRR, (2024)Measuring the Effect of Training Data on Deep Learning Predictions via Randomized Experiments., , , , , and . ICML, volume 162 of Proceedings of Machine Learning Research, page 13468-13504. PMLR, (2022)