2021
DOI: 10.1088/1742-5468/abdc16
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Surfing on minima of isostatic landscapes: avalanches and unjamming transition

Abstract: Recently, we showed that optimization problems, both in infinite as well as in finite dimensions, for continuous variables and soft excluded volume constraints, can display entire isostatic phases where local minima of the cost function are marginally stable configurations endowed with non-linear excitations [, ]. In this work we describe an athermal adiabatic algorithm to explore with continuity the corresponding rough high-dimensional landscape. We concentrate on a prototype problem of this kind, the spheric… Show more

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Cited by 3 publications
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“…A special class of such loss minimization problems is obtained whenever the loss function associated to a single data point is continuous and perfectly vanishing when the data point is correctly classified, and positive otherwise, e.g. the so-called squared hinge loss [18][19][20][21][22]. The question then becomes whether a choice of parameters θ exists, such that all data points in the training set are perfectly classified, leading to a zero loss.…”
Section: Introductionmentioning
confidence: 99%
“…A special class of such loss minimization problems is obtained whenever the loss function associated to a single data point is continuous and perfectly vanishing when the data point is correctly classified, and positive otherwise, e.g. the so-called squared hinge loss [18][19][20][21][22]. The question then becomes whether a choice of parameters θ exists, such that all data points in the training set are perfectly classified, leading to a zero loss.…”
Section: Introductionmentioning
confidence: 99%