2 citations · 2 across the 1 of their papers we have counts for
2 papers
cs.LG2020
Efficient Learning of Model Weights via Changing Features During Training
Marcell Beregi-Kovács, Ágnes Baran, András Hajdu
In this paper, we propose a machine learning model, which dynamically changes the features during training. Our main motivation is to update the model in a small content during the…
nucl-th2017★ 2 cited
Matching polynomial tails to the cut-off Woods-Saxon potential
A. Baran, T. Vertse
Cutting off the tail of the Woods-Saxon and generalized Woods-Saxon potentials changes the distribution of the poles of the -matrix considerably. Here we modify the tail of the…