ML: Training dynamics

Machine-learning ideas tagged Training dynamics in the ML taxonomy of the Math2NN corpus.

2 ideas found

Solves: Regularization ML: Training dynamics Clear all

Unverified 2026

Criticality-controlled sparsity schedule

Use the min-plus phase transition as a training-time controller: begin near p = 1/2 to preserve the initial active-state fraction across depth, then move above or below criticality to deliberately remove or create sparse pathways. The controller uses a measurable state variable, the activation zero fraction, rather than an arbitrary regularization coefficient.

Useful6/10

Difficulty5/10

Novelty9/10

Training Stability Regularization Speedup

Paper: Finite-depth scaling and an exact Bernoulli-leaf identity for the min-plus process on the binary tree arXiv:2608.12295

Unverified 2026

Anisotropic Anharmonic Diffusion Layer

Insert a learnable semigroup layer that evolves features according to a positive operator combining frequency damping and spatially varying confinement. Unlike isotropic Gaussian smoothing, the layer can damp selected frequencies differently along different axes and can suppress activations in learned spatial regions, while the positive-semigroup construction prevents amplification.

Useful6/10

Difficulty5/10

Novelty7/10

Architecture Stability Accuracy Regularization

Paper: Sharp Time-Decay Estimates for Fractional Heat Semigroups Associated with Polynomial Anharmonic Oscillators arXiv:2607.17580