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stat.ME2026
Central limit theorems for the outputs of fully convolutional neural networks with time series input
Annika Betken, Giorgio Micali, Johannes Schmidt-Hieber
Deep learning is widely deployed for time series learning tasks such as classification and forecasting. Despite the empirical successes, only little theory has been developed so fa…
stat.ME2026
Ordinal Patterns Based Testing of Spatial Independence in Irregular Spatial Structures
Giorgio Micali, David Garnés-Galindo, Mariano Matilla-García +1
We propose a nonparametric test of spatial independence for data observed on irregular, non-lattice point clouds . For each location $v\in\mat…
stat.ME2024
Differentially Private Algorithms for Linear Queries via Stochastic Convex Optimization
Giorgio Micali, Clement Lezane, Annika Betken
This article establishes a method to answer a finite set of linear queries on a given dataset while ensuring differential privacy. To achieve this, we formulate the corresponding t…