Improved Differentially Private Analysis of Variance

Differentially Private Local Electricity Markets

Privacy-preserving electricity markets have a key role in steering customers towards participation in local electricity markets by guarantying to protect their sensitive information. Moreover, these markets make it possible to statically release and share the market outputs for social good. This paper aims to design a market for local energy communities by implementing Differential Privacy (DP)...

Differentially Private Analysis of Outliers

This paper investigates differentially private analysis of distance-based outliers. The problem of outlier detection is to find a small number of instances that are apparently distant from the remaining instances. On the other hand, the objective of differential privacy is to conceal presence (or absence) of any particular instance. Outlier detection and privacy protection are thus intrinsicall...

Differentially Private Analysis of Graphs

IMPROVED ESTIMATOR OF THE VARIANCE IN THE LINEAR MODEL

The improved estimator of the variance in the general linear model is presented under an asymmetric linex loss function.

Differentially Private Variational Dropout

Deep neural networks with their large number of parameters are highly flexible learning systems. The high flexibility in such networks brings with some serious problems such as overfitting, and regularization is used to address this problem. A currently popular and effective regularization technique for controlling the overfitting is dropout. Often, large data collections required for neural ne...