Beyond Labeling Oracles: What does it mean to steal ML models?

3 October 2023

Papers citing "Beyond Labeling Oracles: What does it mean to steal ML models?"

7 / 7 papers shown

Title
Locking Machine Learning Models into Hardware Eleanor Clifford Adhithya Saravanan Harry Langford Cheng Zhang Yiren Zhao Robert D. Mullins Ilia Shumailov Jamie Hayes 33 0 0 31 May 2024
Neural Networks Efficiently Learn Low-Dimensional Representations with SGD Alireza Mousavi-Hosseini Sejun Park M. Girotti Ioannis Mitliagkas Murat A. Erdogdu MLT 324 48 0 29 Sep 2022
On the Difficulty of Defending Self-Supervised Learning against Model Extraction Adam Dziedzic Nikita Dhawan Muhammad Ahmad Kaleem Jonas Guan Nicolas Papernot MIACV 54 22 0 16 May 2022
Increasing the Cost of Model Extraction with Calibrated Proof of Work Adam Dziedzic Muhammad Ahmad Kaleem Y. Lu Nicolas Papernot FedML MIACV AAML MLAU 63 28 0 23 Jan 2022
Dataset Inference: Ownership Resolution in Machine Learning Pratyush Maini Mohammad Yaghini Nicolas Papernot FedML 72 104 0 21 Apr 2021
Carbon Emissions and Large Neural Network Training David A. Patterson Joseph E. Gonzalez Quoc V. Le Chen Liang Lluís-Miquel Munguía D. Rothchild David R. So Maud Texier J. Dean AI4CE 253 644 0 21 Apr 2021
Cryptanalytic Extraction of Neural Network Models Nicholas Carlini Matthew Jagielski Ilya Mironov FedML MLAU MIACV AAML 72 134 0 10 Mar 2020