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6 papers · 1 filter
Spatio-Temporal Alignments: Optimal transport through space and time
Hicham Janati, Marco Cuturi, Alexandre Gramfort
Comparing data defined over space and time is notoriously hard, because it involves quantifying both spatial and temporal variability, while at the same time taking into account th…
Algorithms of Robust Stochastic Optimization Based on Mirror Descent Method
Anatoli Juditsky, Alexander Nazin, Arkadi Nemirovsky +1
We propose an approach to construction of robust non-Euclidean iterative algorithms for convex composite stochastic optimization based on truncation of stochastic gradients. For su…
Differentially private sub-Gaussian location estimators
Marco Avella-Medina, Victor-Emmanuel Brunel
We tackle the problem of estimating a location parameter with differential privacy guarantees and sub-Gaussian deviations. Recent work in statistics has focused on the study of est…
On the construction of confidence intervals for ratios of expectations
Alexis Derumigny, Lucas Girard, Yannick Guyonvarch
In econometrics, many parameters of interest can be written as ratios of expectations. The main approach to construct confidence intervals for such parameters is the delta method.…
A nonasymptotic law of iterated logarithm for general M-estimators
Victor-Emmanuel Brunel, Arnak S. Dalalyan, Nicolas Schreuder
M-estimators are ubiquitous in machine learning and statistical learning theory. They are used both for defining prediction strategies and for evaluating their precision. In this p…
Group level MEG/EEG source imaging via optimal transport: minimum Wasserstein estimates
Hicham Janati, Thomas Bazeille, Bertrand Thirion +2
Magnetoencephalography (MEG) and electroencephalogra-phy (EEG) are non-invasive modalities that measure the weak electromagnetic fields generated by neural activity. Inferring the…