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Found 4 papers, 1 papers with code
BOSH: An Efficient Meta Algorithm for Decision-based Attacks
Adversarial example generation becomes a viable method for evaluating the robustness of a machine learning model.
ML-LOO: Detecting Adversarial Examples with Feature Attribution
Furthermore, we extend our method to include multi-layer feature attributions in order to tackle the attacks with mixed confidence levels.
Greedy Attack and Gumbel Attack: Generating Adversarial Examples for Discrete Data
We present a probabilistic framework for studying adversarial attacks on discrete data.
History PCA: A New Algorithm for Streaming PCA
In this paper we propose a new algorithm for streaming principal component analysis.
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