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Found 4 papers, 1 papers with code
Detecting Backdoor Attacks on Deep Neural Networks by Activation Clustering
While machine learning (ML) models are being increasingly trusted to make decisions in different and varying areas, the safety of systems using such models has become an increasing concern.
Defending Against Machine Learning Model Stealing Attacks Using Deceptive Perturbations
Machine learning models are vulnerable to simple model stealing attacks if the adversary can obtain output labels for chosen inputs.
Supervised learning of sparse context reconstruction coefficients for data representation and classification
Context of data points, which is usually defined as the other data points in a data set, has been found to play important roles in data representation and classification.
Representing data by sparse combination of contextual data points for classification
In this objective, the reconstruction error is minimized and the coefficient spar- sity is encouraged.
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