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Found 4 papers, 0 papers with code
Differential Privacy for Class-based Data: A Practical Gaussian Mechanism
In this paper, we present a notion of differential privacy (DP) for data that comes from different classes.
Inferring Class Label Distribution of Training Data from Classifiers: An Accuracy-Augmented Meta-Classifier Attack
In this paper we introduce a new type of property inference attack that unlike binary decision problems in literature, aim at inferring the class label distribution of the training data from parameters of ML classifier models.
Grid-Graph Signal Processing (Grid-GSP): A Graph Signal Processing Framework for the Power Grid
The underlying theme of this paper is to explore the various facets of power systems data through the lens of graph signal processing (GSP), laying down the foundations of the Grid-GSP framework.
A User Guide to Low-Pass Graph Signal Processing and its Applications
The notion of graph filters can be used to define generative models for graph data.
