Articles with public access mandates - Adam DziedzicLearn more
Available somewhere: 13
When the curious abandon honesty: Federated learning is not private
F Boenisch, A Dziedzic, R Schuster, AS Shamsabadi, I Shumailov, ...
Euro S&P 2023, 2021
Mandates: US Department of Defense, Natural Sciences and Engineering Research Council …
Flocks of Stochastic Parrots: Differentially Private Prompt Learning for Large Language Models
H Duan, A Dziedzic, N Papernot, F Boenisch
NeurIPS (Neural Information Processing Systems), 2023
Mandates: US Department of Defense, Natural Sciences and Engineering Research Council …
Band-limited Training and Inference for Convolutional Neural Networks
A Dziedzic, I Paparizzos, S Krishnan, A Elmore, M Franklin
ICML (International Conference on Machine Learning), 2019
Mandates: US National Science Foundation
Machine Learning enabled Spectrum Sharing in Dense LTE-U/Wi-Fi Coexistence Scenarios
A Dziedzic, V Sathya, M Rochman, M Ghosh, S Krishnan
IEEE Open Journal of Vehicular Technology, 2020
Mandates: US National Science Foundation
Integrating Real-Time and Batch Processing in a Polystore
J Meehan, S Zdonik, S Tian, Y Tian, N Tatbul, A Dziedzic, A Elmore
HPEC 2016, 2016
Mandates: US National Science Foundation
On the Difficulty of Defending Self-Supervised Learning against Model Extraction
A Dziedzic, N Dhawan, MA Kaleem, J Guan, N Papernot
ICML (International Conference on Machine Learning), 2022
Mandates: US Department of Defense, Natural Sciences and Engineering Research Council …
Dataset Inference for Self-Supervised Models
A Dziedzic, H Duan, MA Kaleem, N Dhawan, J Guan, Y Cattan, ...
NeurIPS (Neural Information Processing Systems), 2022
Mandates: US Department of Defense, Natural Sciences and Engineering Research Council …
Reconstructing individual data points in federated learning hardened with differential privacy and secure aggregation
F Boenisch, A Dziedzic, R Schuster, AS Shamsabadi, I Shumailov, ...
2023 IEEE 8th European Symposium on Security and Privacy (EuroS&P), 241-257, 2023
Mandates: US Department of Defense, Natural Sciences and Engineering Research Council …
Have it your way: Individualized Privacy Assignment for DP-SGD
F Boenisch, C Mühl, A Dziedzic, R Rinberg, N Papernot
NeurIPS (Neural Information Processing Systems), 2023
Mandates: Natural Sciences and Engineering Research Council of Canada
Machine Learning based detection of multiple Wi-Fi BSSs for LTE-U CSAT
V Sathya, A Dziedzic, M Ghosh, S Krishnan
International Conference on Computing, Networking and Communications (ICNC 2020), 2020
Mandates: US National Science Foundation
Sentence Embedding Encoders are Easy to Steal but Hard to Defend
A Dziedzic, F Boenisch, M Jiang, H Duan, N Papernot
ICLR 2023 Workshop on Trustworthy ML, 2023
Mandates: US Department of Defense, Natural Sciences and Engineering Research Council …
Bucks for Buckets (B4B): Active Defenses Against Stealing Encoders
J Dubiński, S Pawlak, F Boenisch, T Trzciński, A Dziedzic
NeurIPS (Neural Information Processing Systems), 2023
Mandates: National Science Centre, Poland
Robust and Actively Secure Serverless Collaborative Learning
O Franzese, A Dziedzic, CA Choquette-Choo, MR Thomas, MA Kaleem, ...
NeurIPS (Neural Information Processing Systems), 2023
Mandates: US National Science Foundation, US Department of Defense, Natural Sciences …
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