Mathias Lécuyer

Orcid: 0000-0001-9828-1688

According to our database1, Mathias Lécuyer authored at least 28 papers between 2013 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
PANORAMIA: Privacy Auditing of Machine Learning Models without Retraining.
CoRR, 2024

DP-AdamBC: Your DP-Adam Is Actually DP-SGD (Unless You Apply Bias Correction).
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
NetShaper: A Differentially Private Network Side-Channel Mitigation System.
CoRR, 2023

Boost: Effective Caching in Differentially-Private Databases.
CoRR, 2023

DP-Adam: Correcting DP Bias in Adam's Second Moment Estimation.
CoRR, 2023

Turbo: Effective Caching in Differentially-Private Databases.
Proceedings of the 29th Symposium on Operating Systems Principles, 2023

2022
Packing Privacy Budget Efficiently.
CoRR, 2022

GlueFL: Reconciling Client Sampling and Model Masking for Bandwidth Efficient Federated Learning.
CoRR, 2022

Fast Optimization of Weighted Sparse Decision Trees for use in Optimal Treatment Regimes and Optimal Policy Design.
CoRR, 2022

Measuring the Effect of Training Data on Deep Learning Predictions via Randomized Experiments.
Proceedings of the International Conference on Machine Learning, 2022

Fast optimization of weighted sparse decision trees for use in optimal treatment regimes and optimal policy design.
Proceedings of the CIKM 2022 Workshops co-located with 31st ACM International Conference on Information and Knowledge Management (CIKM 2022), 2022

2021
Practical Privacy Filters and Odometers with Rényi Differential Privacy and Applications to Differentially Private Deep Learning.
CoRR, 2021

Privacy Budget Scheduling.
Proceedings of the 15th USENIX Symposium on Operating Systems Design and Implementation, 2021

Sayer: Using Implicit Feedback to Optimize System Policies.
Proceedings of the SoCC '21: ACM Symposium on Cloud Computing, 2021

2019
Security, Privacy, and Transparency Guarantees for Machine Learning Systems.
PhD thesis, 2019

Privacy Accounting and Quality Control in the Sage Differentially Private ML Platform.
ACM SIGOPS Oper. Syst. Rev., 2019

Certified Robustness to Adversarial Examples with Differential Privacy.
Proceedings of the 2019 IEEE Symposium on Security and Privacy, 2019

2018
Enhancing Selectivity in Big Data.
IEEE Secur. Priv., 2018

On the Connection between Differential Privacy and Adversarial Robustness in Machine Learning.
CoRR, 2018

2017
Improving the Transparency of the Sharing Economy.
Proceedings of the 26th International Conference on World Wide Web Companion, 2017

Pyramid: Enhancing Selectivity in Big Data Protection with Count Featurization.
Proceedings of the 2017 IEEE Symposium on Security and Privacy, 2017

Harvesting Randomness to Optimize Distributed Systems.
Proceedings of the 16th ACM Workshop on Hot Topics in Networks, Palo Alto, CA, USA, 2017

2015
Web Transparency for Complex Targeting: Algorithms, Limits, and Tradeoffs.
Proceedings of the 2015 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems, 2015

Synapse: a microservices architecture for heterogeneous-database web applications.
Proceedings of the Tenth European Conference on Computer Systems, 2015

Sunlight: Fine-grained Targeting Detection at Scale with Statistical Confidence.
Proceedings of the 22nd ACM SIGSAC Conference on Computer and Communications Security, 2015

2014
XRay: Enhancing the Web's Transparency with Differential Correlation.
Proceedings of the 23rd USENIX Security Symposium, San Diego, CA, USA, August 20-22, 2014., 2014

2013
Weaving a safe web of news.
Proceedings of the 22nd International World Wide Web Conference, 2013

Dispatch: secure, resilient mobile reporting.
Proceedings of the ACM SIGCOMM 2013 Conference, 2013


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