Apr 15, 2020 · The second main contribution is a new algorithm optimizing both representations and weights of each source for multi-source domain adaptation.

Feb 25, 2021 · The second main contribution is a new algorithm optimizing both representations and weights of each source for multi-source domain adaptation.

We consider the problem of unsupervised domain adaptation from multiple sources in a regression setting. We propose in this work an original method to take ...

We consider the problem of unsupervised domain adaptation from multiple sources in a regression setting. We propose in this work an original method to take ...

Leveraging unsupervised data and domain adaptation for deep regression in low-cost sensor calibration · Environmental Science, Computer Science. IEEE ...

Dec 9, 2023 · Multi-source domain adaptation (DA) aims at leveraging information from more than one source domain to make predictions in a target domain, ...

Code for Unsupervised Multi-Source Domain Adaptation for Regression [1] paper. Every experiment was made using CUDA Drivers 9.0 and a Linux machine.

Multi-source domain adaptation (DA) aims at leveraging information from more than one source domain to make predictions in a target domain, where different ...

Aug 15, 2023 · We propose a new domain adaptation method for regression tasks. Our proposed method adapts domains with any arbitrary shift, concept, or covariate.

May 15, 2022 · We present a novel framework that addresses both problems and beats the current state of the art by using a mildly optimistic objective function and ...