CLuP practically achieves $\sim 1.77$ positive and $\sim 0.33$ negative Hopfield model ground state free energy
Mihailo Stojnic

TL;DR
This paper introduces CLuP algorithms for efficiently approximating ground state energies of positive and negative Hopfield models, achieving near-optimal results with theoretical and practical validation, and revealing intrinsic differences between the models.
Contribution
The paper develops CLuP-based algorithms for Hopfield models and provides theoretical analysis and empirical results demonstrating their effectiveness and insights into model differences.
Findings
CLuP algorithms achieve ground state energy approximations of ~1.77 (positive) and ~0.33 (negative).
Theoretical limits closely match practical performance for small to moderate sizes.
Positive and negative Hopfield models exhibit fundamentally different configuration proximities.
Abstract
We study algorithmic aspects of finding -dimensional \emph{positive} and \emph{negative} Hopfield (Hop) model ground state free energies. This corresponds to classical maximization of random positive/negative semi-definite quadratic forms over binary vectors. The key algorithmic question is whether these problems can be computationally efficiently approximated within a factor . Following the introduction and success of \emph{Controlled Loosening-up} (CLuP-SK) algorithms in finding near ground state energies of closely related Sherrington-Kirkpatrick (SK) models [82], we here propose a CLuPHop counterparts for Hop models. Fully lifted random duality theory (fl RDT) [78] is utilized to characterize CLuPHop \emph{typical} dynamics. An excellent agreement between practical performance and theoretical predictions…
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