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Mathias Lécuyer
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2020 – today
- 2024
- [c20]Qiaoyue Tang, Frederick Shpilevskiy, Mathias Lécuyer:
DP-AdamBC: Your DP-Adam Is Actually DP-SGD (Unless You Apply Bias Correction). AAAI 2024: 15276-15283 - [c19]Pierre Tholoniat
, Kelly Kostopoulou
Cookie Monster: Efficient On-Device Budgeting for Differentially-Private Ad-Measurement Systems. SOSP 2024: 693-708 - [c18]Amir Sabzi, Rut Vora, Swati Goswami, Margo I. Seltzer, Mathias Lécuyer, Aastha Mehta:
NetShaper: A Differentially Private Network Side-Channel Mitigation System. USENIX Security Symposium 2024 - [i20]Mishaal Kazmi, Hadrien Lautraite, Alireza Akbari, Mauricio Soroco, Qiaoyue Tang, Tao Wang, Sébastien Gambs, Mathias Lécuyer:
PANORAMIA: Privacy Auditing of Machine Learning Models without Retraining. CoRR abs/2402.09477 (2024) - [i19]Bingshan Hu, Zhiming Huang
Efficient and Adaptive Posterior Sampling Algorithms for Bandits. CoRR abs/2405.01010 (2024) - [i18]Pierre Tholoniat, Kelly Kostopoulou, Peter McNeely, Prabhpreet Singh Sodhi, Anirudh Varanasi, Benjamin Case, Asaf Cidon, Roxana Geambasu, Mathias Lécuyer:
Alistair: Efficient On-device Budgeting for Differentially-Private Ad-Measurement Systems. CoRR abs/2405.16719 (2024) - [i17]Saiyue Lyu, Shadab Shaikh, Frederick Shpilevskiy, Evan Shelhamer, Mathias Lécuyer:
Adaptive Randomized Smoothing: Certifying Multi-Step Defences against Adversarial Examples. CoRR abs/2406.10427 (2024) - [i16]Thomas Crasson, Yacine Nabet, Mathias Lécuyer:
Training and Evaluating Causal Forecasting Models for Time-Series. CoRR abs/2411.00126 (2024) - 2023
- [c17]Shiqi He, Qifan Yan, Feijie Wu, Lanjun Wang, Mathias Lécuyer, Ivan Beschastnikh:
GlueFL: Reconciling Client Sampling and Model Masking for Bandwidth Efficient Federated Learning. MLSys 2023 - [c16]Kelly Kostopoulou
Turbo: Effective Caching in Differentially-Private Databases. SOSP 2023: 579-594 - [i15]Qiaoyue Tang, Mathias Lécuyer:
DP-Adam: Correcting DP Bias in Adam's Second Moment Estimation. CoRR abs/2304.11208 (2023) - [i14]Kelly Kostopoulou, Pierre Tholoniat, Asaf Cidon, Roxana Geambasu, Mathias Lécuyer:
Boost: Effective Caching in Differentially-Private Databases. CoRR abs/2306.16163 (2023) - [i13]Amir Sabzi, Rut Vora, Swati Goswami, Margo I. Seltzer, Mathias Lécuyer, Aastha Mehta:
NetShaper: A Differentially Private Network Side-Channel Mitigation System. CoRR abs/2310.06293 (2023) - [i12]Qiaoyue Tang, Frederick Shpilevskiy, Mathias Lécuyer:
DP-AdamBC: Your DP-Adam Is Actually DP-SGD (Unless You Apply Bias Correction). CoRR abs/2312.14334 (2023) - 2022
- [c15]Ali Behrouz, Mathias Lécuyer, Cynthia Rudin, Mango I. Seltzer:
Fast optimization of weighted sparse decision trees for use in optimal treatment regimes and optimal policy design. CIKM Workshops 2022 - [c14]Jinkun Lin, Anqi Zhang, Mathias Lécuyer, Jinyang Li, Aurojit Panda, Siddhartha Sen:
Measuring the Effect of Training Data on Deep Learning Predictions via Randomized Experiments. ICML 2022: 13468-13504 - [i11]Jinkun Lin, Anqi Zhang, Mathias Lécuyer, Jinyang Li, Aurojit Panda, Siddhartha Sen:
Measuring the Effect of Training Data on Deep Learning Predictions via Randomized Experiments. CoRR abs/2206.10013 (2022) - [i10]Ali Behrouz, Mathias Lécuyer, Cynthia Rudin, Margo I. Seltzer:
Fast Optimization of Weighted Sparse Decision Trees for use in Optimal Treatment Regimes and Optimal Policy Design. CoRR abs/2210.06825 (2022) - [i9]Shiqi He, Qifan Yan, Feijie Wu, Lanjun Wang, Mathias Lécuyer, Ivan Beschastnikh:
GlueFL: Reconciling Client Sampling and Model Masking for Bandwidth Efficient Federated Learning. CoRR abs/2212.01523 (2022) - [i8]Pierre Tholoniat, Kelly Kostopoulou, Mosharaf Chowdhury, Asaf Cidon, Roxana Geambasu, Mathias Lécuyer, Junfeng Yang:
Packing Privacy Budget Efficiently. CoRR abs/2212.13228 (2022) - 2021
- [c13]Mathias Lécuyer, Sang Hoon Kim, Mihir Nanavati, Junchen Jiang, Siddhartha Sen, Aleksandrs Slivkins, Amit Sharma:
Sayer: Using Implicit Feedback to Optimize System Policies. SoCC 2021: 273-288 - [c12]Tao Luo, Mingen Pan, Pierre Tholoniat, Asaf Cidon, Roxana Geambasu, Mathias Lécuyer:
Privacy Budget Scheduling. OSDI 2021: 55-74 - [i7]Mathias Lécuyer:
Practical Privacy Filters and Odometers with Rényi Differential Privacy and Applications to Differentially Private Deep Learning. CoRR abs/2103.01379 (2021) - [i6]Tao Luo, Mingen Pan, Pierre Tholoniat, Asaf Cidon, Roxana Geambasu, Mathias Lécuyer:
Privacy Budget Scheduling. CoRR abs/2106.15335 (2021) - [i5]Mathias Lécuyer, Sang Hoon Kim, Mihir Nanavati, Junchen Jiang, Siddhartha Sen, Amit Sharma, Aleksandrs Slivkins:
Sayer: Using Implicit Feedback to Optimize System Policies. CoRR abs/2110.14874 (2021)
2010 – 2019
- 2019
- [b1]Mathias Lécuyer:
Security, Privacy, and Transparency Guarantees for Machine Learning Systems. Columbia University, USA, 2019 - [j2]Mathias Lécuyer, Riley Spahn, Kiran Vodrahalli, Roxana Geambasu, Daniel Hsu:
Privacy Accounting and Quality Control in the Sage Differentially Private ML Platform. ACM SIGOPS Oper. Syst. Rev. 53(1): 75-84 (2019) - [c11]Mathias Lécuyer, Riley Spahn, Kiran Vodrahalli, Roxana Geambasu, Daniel Hsu:
Privacy accounting and quality control in the sage differentially private ML platform. SOSP 2019: 181-195 - [c10]Mathias Lécuyer, Vaggelis Atlidakis, Roxana Geambasu, Daniel Hsu, Suman Jana:
Certified Robustness to Adversarial Examples with Differential Privacy. IEEE Symposium on Security and Privacy 2019: 656-672 - [i4]Mathias Lécuyer, Riley Spahn, Kiran Vodrahalli, Roxana Geambasu, Daniel Hsu:
Privacy Accounting and Quality Control in the Sage Differentially Private ML Platform. CoRR abs/1909.01502 (2019) - 2018
- [j1]Mathias Lécuyer, Riley Spahn, Roxana Geambasu, Tzu-Kuo Huang, Siddhartha Sen:
Enhancing Selectivity in Big Data. IEEE Secur. Priv. 16(1): 34-42 (2018) - [i3]Mathias Lécuyer, Vaggelis Atlidakis, Roxana Geambasu, Daniel Hsu, Suman Jana:
On the Connection between Differential Privacy and Adversarial Robustness in Machine Learning. CoRR abs/1802.03471 (2018) - 2017
- [c9]Mathias Lécuyer, Joshua Lockerman, Lamont Nelson, Siddhartha Sen, Amit Sharma, Aleksandrs Slivkins:
Harvesting Randomness to Optimize Distributed Systems. HotNets 2017: 178-184 - [c8]Mathias Lécuyer, Riley Spahn, Roxana Geambasu, Tzu-Kuo Huang, Siddhartha Sen:
Pyramid: Enhancing Selectivity in Big Data Protection with Count Featurization. IEEE Symposium on Security and Privacy 2017: 78-95 - [c7]Mathias Lécuyer, Max Tucker, Augustin Chaintreau
Improving the Transparency of the Sharing Economy. WWW (Companion Volume) 2017: 1043-1051 - [i2]Mathias Lécuyer, Riley Spahn, Roxana Geambasu, Tzu-Kuo Huang, Siddhartha Sen:
Pyramid: Enhancing Selectivity in Big Data Protection with Count Featurization. CoRR abs/1705.07512 (2017) - 2015
- [c6]Mathias Lécuyer, Riley Spahn, Yannis Spiliopolous, Augustin Chaintreau
Sunlight: Fine-grained Targeting Detection at Scale with Statistical Confidence. CCS 2015: 554-566 - [c5]Nicolas Viennot, Mathias Lécuyer, Jonathan Bell, Roxana Geambasu, Jason Nieh:
Synapse: a microservices architecture for heterogeneous-database web applications. EuroSys 2015: 21:1-21:16 - [c4]Guillaume Ducoffe, Mathias Lécuyer, Augustin Chaintreau
Web Transparency for Complex Targeting: Algorithms, Limits, and Tradeoffs. SIGMETRICS 2015: 465-466 - 2014
- [c3]Mathias Lécuyer, Guillaume Ducoffe, Francis Lan, Andrei Papancea, Theofilos Petsios, Riley Spahn, Augustin Chaintreau, Roxana Geambasu:
XRay: Enhancing the Web's Transparency with Differential Correlation. USENIX Security Symposium 2014: 49-64 - [i1]Mathias Lécuyer, Guillaume Ducoffe, Francis Lan, Andrei Papancea, Theofilos Petsios, Riley Spahn, Augustin Chaintreau, Roxana Geambasu:
XRay: Enhancing the Web's Transparency with Differential Correlation. CoRR abs/1407.2323 (2014) - 2013
- [c2]Kanak Biscuitwala, Willem Bult, Mathias Lécuyer, T. J. Purtell, Madeline K. B. Ross, Augustin Chaintreau
Dispatch: secure, resilient mobile reporting. SIGCOMM 2013: 459-460 - [c1]Kanak Biscuitwala, Willem Bult, Mathias Lécuyer, T. J. Purtell, Madeline K. B. Ross, Augustin Chaintreau, Chris Haseman, Monica S. Lam, Susan E. McGregor:
Weaving a safe web of news. WWW (Companion Volume) 2013: 849-852
Coauthor Index
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