ML: Scalability

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

2 ideas found

Status: Unverified ML: Scalability Clear all

Unverified 2026

Degree-Capped Simplicial Residual Step

Set the residual propagation coefficient of a simplicial neural layer from a cheap upper bound on the operator spectrum instead of tuning it blindly. The degree-majorization theorem supplies a bound on the largest eigenvalue, while the Brouwer-type inequality supplies a topology-count-based bound on sums of the top eigenvalues.

Useful6/10

Difficulty3/10

Novelty6/10

Architecture Stability Speedup Scalability

Paper: Degree Majorization and Laplacian Eigenvalue Sums for Simplicial Complexes arXiv:2607.20910

Unverified 2026

Additive-energy sparse offset design

Learn or select sparse cyclic convolution or relative-attention offsets whose pairwise differences collide less often modulo the sequence length. The paper's Fourier fourth-power identity turns this combinatorial objective into an FFT-computable differentiable loss, enabling fixed-K sparse patterns with lower aliasing and interference than random offsets.

Useful5/10

Difficulty4/10

Novelty7/10

Architecture Accuracy Scalability Memory

Paper: Spectral and Additive Combinatorial Methods for Cycles and Absorbing Sets in Lifted-Product Quantum LDPC Codes arXiv:2607.13666