3 papers
cs.LG2026
STARFISH: faST Accuracy Recovery in pruned networks From Internal State Healing
Shir Maon, Odelia Melamed, Adi Shamir
Pruning is a process designed to reduce the number of weights in a large neural network. This can substantially speed up inference but might cause a considerable reduction in the m…
cs.CR2024
Polynomial Time Cryptanalytic Extraction of Deep Neural Networks in the Hard-Label Setting
Nicholas Carlini, Jorge Chávez-Saab, Anna Hambitzer +2
Deep neural networks (DNNs) are valuable assets, yet their public accessibility raises security concerns about parameter extraction by malicious actors. Recent work by Carlini et a…
cs.LG2023
Polynomial Time Cryptanalytic Extraction of Neural Network Models
Adi Shamir, Isaac Canales-Martinez, Anna Hambitzer +3
Billions of dollars and countless GPU hours are currently spent on training Deep Neural Networks (DNNs) for a variety of tasks. Thus, it is essential to determine the difficulty of…