4 citations · 6 across the 22 of their papers we have counts for
Showing 2024Show all
2 papers · 1 filter
cs.LG2024
Improving Robustness of Spectrogram Classifiers with Neural Stochastic Differential Equations
Joel Brogan, Olivera Kotevska, Anibely Torres +2
Signal analysis and classification is fraught with high levels of noise and perturbation. Computer-vision-based deep learning models applied to spectrograms have proven useful in t…
cs.CR2024★ 1 cited
Dealing Doubt: Unveiling Threat Models in Gradient Inversion Attacks under Federated Learning, A Survey and Taxonomy
Yichuan Shi, Olivera Kotevska, Viktor Reshniak +2
Federated Learning (FL) has emerged as a leading paradigm for decentralized, privacy preserving machine learning training. However, recent research on gradient inversion attacks (G…