6 citations · 8 across the 3 of their papers we have counts for
3 papers
On the Importance of Hyperparameters and Data Augmentation for Self-Supervised Learning
Diane Wagner, Fabio Ferreira, Danny Stoll +3
Self-Supervised Learning (SSL) has become a very active area of Deep Learning research where it is heavily used as a pre-training method for classification and other tasks. However…
Smart(Sampling)Augment: Optimal and Efficient Data Augmentation for Semantic Segmentation
Misgana Negassi, Diane Wagner, Alexander Reiterer
Data augmentation methods enrich datasets with augmented data to improve the performance of neural networks. Recently, automated data augmentation methods have emerged, which autom…
Hyperparameter Transfer Across Developer Adjustments
Danny Stoll, Jörg K. H. Franke, Diane Wagner +2
After developer adjustments to a machine learning (ML) algorithm, how can the results of an old hyperparameter optimization (HPO) automatically be used to speedup a new HPO? This q…