A gradient-weighted, data-dependent polynomial norm makes approximate border basis computation invariant to data scaling and more stable to perturbations than coefficient normalization.
Emiris, editors
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.SC 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Gradient-Weighted, Data-Driven Normalization for Approximate Border Bases -- Concept and Computation
A gradient-weighted, data-dependent polynomial norm makes approximate border basis computation invariant to data scaling and more stable to perturbations than coefficient normalization.