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Michael Teti

2 accepted papers

2024

Improving Robustness to Model Inversion Attacks via Sparse Coding Architectures

ECCV 2024poster

"Recent model inversion attack algorithms permit adversaries to reconstruct a neural network’s private and potentially sensitive training data by repeatedly querying the network. In this work, we develop a novel network architecture that leverages sparse-coding layers to obtain superior robustness t…

2022

LCANets: Lateral Competition Improves Robustness Against Corruption and Attack

ICML 2022spotlight

Although Convolutional Neural Networks (CNNs) achieve high accuracy on image recognition tasks, they lack robustness against realistic corruptions and fail catastrophically when deliberately attacked. Previous CNNs with representations similar to primary visual cortex (V1) were more robust to advers…

Cited by 25SourcePDFScholar