The Canonical Evolutionary Strategy converges globally by spectral concentration on the principal eigenfunction of a replicator-mutator operator, explaining survival of the flattest.
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Random Matrix Theory detects overfitting via growing Correlation Traps in weight spectra during the anti-grokking phase of neural network training.
Adiabatic temperature change in Mn1.3Fe0.7P0.5Si0.55 is field-sweep-rate independent due to paramagnetic moment alignment overlapping the first-order transition, which remains incomplete up to 20 T and shows field-dependent hysteresis in pulsed fields.
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Detecting overfitting in Neural Networks during long-horizon grokking using Random Matrix Theory
Random Matrix Theory detects overfitting via growing Correlation Traps in weight spectra during the anti-grokking phase of neural network training.