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Automatic L2 Regularization for Multiple Generalized Additive Models

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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

Automatic L2 Regularization for Multiple Generalized Additive Models

Graph Chatbot

Chattez avec Graph Search

Machine learning models for prediction of electrochemical properties in supercapacitor electrodes using MXene and graphene nanoplatelets

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

Distributional Regression and Autoregression via Optimal Transport

Distribution-on-distribution regression via optimal transport maps

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

Are green bonds priced lower than their conventional peers?

Fast screening of covariates in population models empowered by machine learning

Improving sample and feature selection with principal covariates regression

Multi-ion-sensing emulator and multivariate calibration optimization by machine learning models

Sparsest piecewise-linear regression of one-dimensional data

Machine learning models for prediction of electrochemical properties in supercapacitor electrodes using MXene and graphene nanoplatelets

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

Distribution-on-distribution regression via optimal transport maps

Are green bonds priced lower than their conventional peers?

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

Multi-ion-sensing emulator and multivariate calibration optimization by machine learning models

Distributional Regression and Autoregression via Optimal Transport

Sparsest piecewise-linear regression of one-dimensional data

Fast screening of covariates in population models empowered by machine learning

Improving sample and feature selection with principal covariates regression