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Found 3 papers, 0 papers with code
On the Importance of Architecture and Feature Selection in Differentially Private Machine Learning
The use of differentially private learning algorithms in a "drop-in" fashion -- without accounting for the impact of differential privacy (DP) noise when choosing what feature engineering operations to use, what features to select, or what neural network architecture to use -- yields overly complex and poorly performing models.
Attacks as Defenses: Designing Robust Audio CAPTCHAs Using Attacks on Automatic Speech Recognition Systems
We begin by comparing 20 recent attack papers, classifying and measuring their suitability to serve as the basis of new "robust to transcription" but "easy for humans to understand" CAPTCHAs.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
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Covert Message Passing over Public Internet Platforms Using Model-Based Format-Transforming Encryption
We introduce a new type of format-transforming encryption where the format of ciphertexts is implicitly encoded within a machine-learned generative model.
