Unsupervised Robust Domain Adaptation without Source Data

no code implementations • 26 Mar 2021 • Peshal Agarwal, Danda Pani Paudel, Jan-Nico Zaech, Luc van Gool

This paper aims at answering the question of finding the right strategy to make the target model robust and accurate in the setting of unsupervised domain adaptation without source data.

Image Classification Unsupervised Domain Adaptation

SnapBoost: A Heterogeneous Boosting Machine

2 code implementations • NeurIPS 2020 • Thomas Parnell, Andreea Anghel, Malgorzata Lazuka, Nikolas Ioannou, Sebastian Kurella, Peshal Agarwal, Nikolaos Papandreou, Haralampos Pozidis

At each boosting iteration, their goal is to find the base hypothesis, selected from some base hypothesis class, that is closest to the Newton descent direction in a Euclidean sense.