Dynamical Low-Rank Compression of Neural Networks with Robustness under Adversarial Attacks

NeurIPSOral2025

Authors
Steffen Schotthöfer, H. Lexie Yang, Stefan Schnake
Affiliation
Oak Ridge National Laboratory
Venue
NeurIPS 2025
Track
Oral

TL;DR

Deployment of neural networks on resource-constrained devices demands models that are both compact and robust to adversarial inputs. However, compression and adversarial robustness often conflict.

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Topics

adversarial robustness

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