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Sparsest piecewise-linear regression of one-dimensional data

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Distributional Regression and Autoregression via Optimal Transport

Laya Ghodrati

We present a framework for performing regression when both covariate and response are probability distributions on a compact and convex subset of

\R^d

. Our regression model is based on the theory of optimal transport and links the conditional Fr'echet m ...

EPFL2023

Sparsest piecewise-linear regression of one-dimensional data

Graph Chatbot

Chat with Graph Search

Bayes-optimal Learning of Deep Random Networks of Extensive-width

Distributional Regression and Autoregression via Optimal Transport

Acute TNF alpha levels predict cognitive impairment 6-9 months after COVID-19 infection

(S)GD over Diagonal Linear Networks: Implicit Regularisation, Large Stepsizes and Edge of Stability

Distribution-on-distribution regression via optimal transport maps

Minimax rate for optimal transport regression between distributions

Fast screening of covariates in population models empowered by machine learning

Improving sample and feature selection with principal covariates regression

Adaptive hot water production based on Supervised Learning

A Global-Local Approach For Detecting Hotspots In Multiple-Response Regression

Acute TNF alpha levels predict cognitive impairment 6-9 months after COVID-19 infection

(S)GD over Diagonal Linear Networks: Implicit Regularisation, Large Stepsizes and Edge of Stability

Distribution-on-distribution regression via optimal transport maps

Bayes-optimal Learning of Deep Random Networks of Extensive-width

Minimax rate for optimal transport regression between distributions

Distributional Regression and Autoregression via Optimal Transport

Improving sample and feature selection with principal covariates regression

A Global-Local Approach For Detecting Hotspots In Multiple-Response Regression

Fast screening of covariates in population models empowered by machine learning

Adaptive hot water production based on Supervised Learning