Abstract: Faced with massive data, subsampling is a commonly used technique to improve computational efficiency, and using nonuniform subsampling probabilities is an effective approach to improve ...

The Poisson probability distribution is frequently encountered in physical science measurements. In spite of the simplicity and familiarity of this distribution, there is considerable confusion among ...

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Differentially Private Stochastic Gradient Descent (DP-SGD) is a key method for training machine learning models like neural networks while ensuring privacy. It modifies the standard gradient descent ...

Sampling is a technique in which samples are drawn at random (without any favor or bias). For this, suitable measures or procedures may be laid down and adopted according to the nature and ...

Abstract: Packet sampling measurement is a key technique in high-speed network traffic monitoring and management. In this paper, packet sampling techniques are introduced and analyzed after the ...