A gradient-similarity complexity measure that generalizes polynomial degree, kernel length scale, neighbor count, tree splits, and forest size while offering insights into double descent.
IEEE transactions on neural networks and learning systems , volume=
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A Rigorous, Tractable Measure of Model Complexity
A gradient-similarity complexity measure that generalizes polynomial degree, kernel length scale, neighbor count, tree splits, and forest size while offering insights into double descent.