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Benchmarking Adversarial Robustness of Compressed Deep Learning Models
Our findings reveal that while the benefits of pruning enhanced generalizability, compression, and faster inference times are preserved, adversarial robustness remains comparable to the base model.
Gimme That Model!: A Trusted ML Model Trading Protocol
We propose a HE-based protocol for trading ML models and describe possible improvements to the protocol to make the overall transaction more efficient and secure.
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