5 citations · 7 across the 4 of their papers we have counts for
4 papers
AutoDrop: Training Deep Learning Models with Automatic Learning Rate Drop
Yunfei Teng, Jing Wang, Anna Choromanska
Modern deep learning (DL) architectures are trained using variants of the SGD algorithm that is run with a defined learning rate schedule, i.e., the learning ra…
Overcoming Catastrophic Forgetting via Direction-Constrained Optimization
Yunfei Teng, Anna Choromanska, Murray Campbell +3
This paper studies a new design of the optimization algorithm for training deep learning models with a fixed architecture of the classification network in a continual learning fram…
Leader Stochastic Gradient Descent for Distributed Training of Deep Learning Models: Extension
Yunfei Teng, Wenbo Gao, Francois Chalus +3
We consider distributed optimization under communication constraints for training deep learning models. We propose a new algorithm, whose parameter updates rely on two forces: a re…
Invertible Autoencoder for domain adaptation
Yunfei Teng, Anna Choromanska, Mariusz Bojarski
The unsupervised image-to-image translation aims at finding a mapping between the source () and target () image domains, where in many applications aligned image pairs are no…