CLuP practically achieves positive and negative Hopfield model ground state free energy

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 is observed. In particular, for as small as few thousands CLuPHop achieve and as the ground state free energies of the positive and negative Hopfield models. At the same time we obtain on the 6th level of lifting (6-spl RDT) corresponding theoretical thermodynamic () limits and . This positions determining Hopfield models near ground state energies as \emph{typically} easy problems. Moreover, the very same 6th lifting level evaluations allow to uncover a fundamental intrinsic difference between two models: Hop's near optimal configurations are \emph{typically close} to each other whereas the Hop's are \emph{typically far away}.
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