Matthew Jagielski Empirically Auditing Privacy In Machine Learning

By Editorial Team · October 2, 2026 · 8 min read

Matthew Jagielski Empirically Auditing Privacy In Machine Learning Information Guide

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Information Matthew Jagielski @ TPDP 2020 Guide
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Machine Learning Security Seminar Series - Matthew Jagielski News
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USENIX Enigma 2022 - Auditing Data Privacy for Machine Learning
USENIX Enigma 2022 - Auditing Data Privacy for Machine Learning
USENIX Security '23 - Tight Auditing of Differentially Private Machine Learning
USENIX Security '23 - Tight Auditing of Differentially Private Machine Learning
Matthew Jagielski (Google Research), Some Results on Privacy and Machine Unlearning
Matthew Jagielski (Google Research), Some Results on Privacy and Machine Unlearning
Security and Privacy of Machine Learning
Security and Privacy of Machine Learning
[3B] How to Combine Membership-Inference Attacks on Multiple Updated Machine Learning Models
[3B] How to Combine Membership-Inference Attacks on Multiple Updated Machine Learning Models
USENIX Security '24 - Efficient Privacy Auditing in Federated Learning
USENIX Security '24 - Efficient Privacy Auditing in Federated Learning
Reza Shokri (NUS), Privacy Auditing in Machine Learning
Reza Shokri (NUS), Privacy Auditing in Machine Learning
How to Build Privacy and Security Into Deep Learning Models – Mr. Yishay Carmiel
How to Build Privacy and Security Into Deep Learning Models – Mr. Yishay Carmiel
Nicolas Papernot | A Marauder's Map of Security and Privacy in Machine Learning
Nicolas Papernot | A Marauder's Map of Security and Privacy in Machine Learning
The Limits and Possibilities of One Run Auditing
The Limits and Possibilities of One Run Auditing
Yang Zhang - Quantifying Privacy Risks of Machine Learning Models
Yang Zhang - Quantifying Privacy Risks of Machine Learning Models

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Last Updated: October 2, 2026

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Summary

This talk will cover three research directions pertinent to the DP community and relevant in modern Ian Goodfellow, Staff Research Scientist, Google Brain 'How to Combine Membership-Inference Attacks on Multiple Updated Prof. Reza Shokri, National University of Singapore, The founder of intelligent wire company that develops and implements There is growing recognition that A Google TechTalk, 2025-12-10, presented by Moshe Shenfeld Yang Zhang gave this talk as part of the ViSP Distinguished Lecture Series ( visp.wien/lecture-series). Abstract:

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