2 citations · 2 across the 2 of their papers we have counts for
3 papers
cs.LG2026
D-SLR: The Disjoint Row-Sparse plus Low-Rank Decomposition
Vincent Szolnoky
Compressing a matrix for reconstruction still defaults to the truncated SVD, approximating the data with a single low-rank structure. It is common to reduce the residual further by…
math.OC2023
Controlled Descent Training
Viktor Andersson, Balázs Varga, Vincent Szolnoky +3
In this work, a novel and model-based artificial neural network (ANN) training method is developed supported by optimal control theory. The method augments training labels in order…
stat.ML2022★ 2 cited
On the Interpretability of Regularisation for Neural Networks Through Model Gradient Similarity
Vincent Szolnoky, Viktor Andersson, Balazs Kulcsar +1
Most complex machine learning and modelling techniques are prone to over-fitting and may subsequently generalise poorly to future data. Artificial neural networks are no different…