2 papers
cs.LG2026
Sparse Training of Neural Networks based on Multilevel Mirror Descent
Yannick Lunk, Sebastian J. Scott, Leon Bungert
We introduce a dynamic sparse training algorithm based on linearized Bregman iterations / mirror descent that exploits the naturally incurred sparsity by alternating between period…
math.OC2025
Efficient gradient-based methods for bilevel learning via recycling Krylov subspaces
Matthias J. Ehrhardt, Silvia Gazzola, Sebastian J. Scott
Many optimization problems require hyperparameters, i.e., parameters that must be pre-specified in advance, such as regularization parameters and parametric regularizers in variati…