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Modeling, Regression and Optimization

Publications associées (46)

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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

Modeling, Regression and Optimization

Graph Chatbot

Chattez avec Graph Search

Distributional Regression and Autoregression via Optimal Transport

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

Distribution-on-distribution regression via optimal transport maps

Minimax rate for optimal transport regression between distributions

One Fuzz Doesn’t Fit All: Optimizing Directed Fuzzing via Target-tailored Program State Restriction

Deep Learning with Convolutional Neural Network for Proportional Control of Finger Movements from surface EMG Recordings

Gaussian Process Regression for Materials and Molecules

Functional lagged regression with sparse noisy observations

Optimal Convergence for Distributed Learning with Stochastic Gradient Methods and Spectral Algorithms

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

Distributional Regression and Autoregression via Optimal Transport

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

Minimax rate for optimal transport regression between distributions

One Fuzz Doesn’t Fit All: Optimizing Directed Fuzzing via Target-tailored Program State Restriction

Deep Learning with Convolutional Neural Network for Proportional Control of Finger Movements from surface EMG Recordings

Distribution-on-distribution regression via optimal transport maps

Gaussian Process Regression for Materials and Molecules

Functional lagged regression with sparse noisy observations

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

Optimal Convergence for Distributed Learning with Stochastic Gradient Methods and Spectral Algorithms