Search Results for author:
Found 6 papers, 0 papers with code
High-dimensional analysis of ridge regression for non-identically distributed data with a variance profile
We also investigate the similarities and differences that exist with the standard setting of independent and identically distributed data.
Stochastic optimal transport in Banach Spaces for regularized estimation of multivariate quantiles
We introduce a new stochastic algorithm for solving entropic optimal transport (EOT) between two absolutely continuous probability measures $\mu$ and $\nu$.
On the potential benefits of entropic regularization for smoothing Wasserstein estimators
This paper is focused on the study of entropic regularization in optimal transport as a smoothing method for Wasserstein estimators, through the prism of the classical tradeoff between approximation and estimation errors in statistics.
Online Graph Topology Learning from Matrix-valued Time Series
Therefore, we augment the proposed AR models by incorporating trend as extra parameter, and then adapt the online algorithms to the augmented data models, which allow us to simultaneously learn the graph and trend from streaming samples.
Sensor selection on graphs via data-driven node sub-sampling in network time series
This paper is concerned by the problem of selecting an optimal sampling set of sensors over a network of time series for the purpose of signal recovery at non-observed sensors with a minimal reconstruction error.
Fréchet random forests for metric space valued regression with non euclidean predictors
Random forests are a statistical learning method widely used in many areas of scientific research because of its ability to learn complex relationships between input and output variables and also its capacity to handle high-dimensional data.
