Gated Domain Units for Multi-source Domain Generalization

1 code implementation • 24 Jun 2022 • Simon Föll, Alina Dubatovka, Eugen Ernst, Siu Lun Chau, Martin Maritsch, Patrik Okanovic, Gudrun Thäter, Joachim M. Buhmann, Felix Wortmann, Krikamol Muandet

To address this problem, we postulate that real-world distributions are composed of latent Invariant Elementary Distributions (I. E. D) across different domains.

Domain Generalization Transfer Learning

Ranking architectures using meta-learning

no code implementations • 26 Nov 2019 • Alina Dubatovka, Efi Kokiopoulou, Luciano Sbaiz, Andrea Gesmundo, Gabor Bartok, Jesse Berent

However, it requires a large amount of computing resources and in order to alleviate this, a performance prediction network has been recently proposed that enables efficient architecture search by forecasting the performance of candidate architectures, instead of relying on actual model training.

Meta-Learning Neural Architecture Search

Initialization of ReLUs for Dynamical Isometry

1 code implementation • NeurIPS 2019 • Rebekka Burkholz, Alina Dubatovka

Deep learning relies on good initialization schemes and hyperparameter choices prior to training a neural network.