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Research PaperResearchia:202609.16018

Bias-Induced Crossover in Absolute Capacity of Dense Associative Memory

Yuto Sakurai

Abstract

The absolute capacity of dense associative memory has mainly been analyzed for unbiased patterns. Here we examine the effect of bias in centered binary patterns under the Krotov-Hopfield single-site criterion $P_{\mathrm{error}}=1/N$, where $P_{\mathrm{error}}$ is the probability that a single-site flip lowers the energy of a stored pattern and $N$ is the number of neurons. Each pattern component takes $1-q$ with probability $q$ and $-q$ otherwise, where $0<q\le1/2$. For polynomial interactions ...

Submitted: September 16, 2026Subjects: Machine Learning; Data Science

Description / Details

The absolute capacity of dense associative memory has mainly been analyzed for unbiased patterns. Here we examine the effect of bias in centered binary patterns under the Krotov-Hopfield single-site criterion Perror=1/NP_{\mathrm{error}}=1/N, where PerrorP_{\mathrm{error}} is the probability that a single-site flip lowers the energy of a stored pattern and NN is the number of neurons. Each pattern component takes 1βˆ’q1-q with probability qq and βˆ’q-q otherwise, where 0<q≀1/20<q\le1/2. For polynomial interactions of order nn, a signal-to-noise analysis gives an absolute capacity of order Nnβˆ’1/ln⁑NN^{n-1}/\ln N at q=1/2q=1/2. For fixed q<1/2q<1/2, however, the capacity is O(Nn/2)O(N^{n/2}) for even nβ‰₯4n\ge4 and O(N(n+1)/2)O(N^{(n+1)/2}) for odd nβ‰₯5n\ge5. For n=3n=3, both the unbiased and fixed-bias capacities remain O(N2/ln⁑N)O(N^2/\ln N). For nβ‰₯4n\ge4, these different asymptotic forms imply a nonuniform large-NN limit near q=1/2q=1/2. Asymptotic matching predicts a bias-induced crossover in the region 1βˆ’2q=O(ln⁑N/N⌊n/2βŒ‹βˆ’1)1-2q=O(\ln N/N^{\lfloor n/2\rfloor-1}). The crossover originates from a bias-dependent crosstalk mean that reduces the stability of sites carrying the more frequent value βˆ’q-q. Computer simulations are compared with the finite-size conditioned-Gaussian predictions. An activity-dependent control potential that cancels the conditional crosstalk mean restores the Nnβˆ’1/ln⁑NN^{n-1}/\ln N capacity for fixed 0<q<1/20<q<1/2 within the conditioned-Gaussian approximation.


Source: arXiv:2609.17477v1 - http://arxiv.org/abs/2609.17477v1 PDF: https://arxiv.org/pdf/2609.17477v1 Original Link: http://arxiv.org/abs/2609.17477v1

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Date:
Sep 16, 2026
Topic:
Data Science
Area:
Machine Learning
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