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The symmetric binary perceptron ($\mathrm{SBP}_{\kappa}$) problem with parameter $\kappa : \mathbb{R}_{\geq1} \to [0,1]$ is an average-case search problem defined as follows: given a random Gaussian matrix $\mathbf{A} \sim…

Statistics Theory · Mathematics 2025-07-29 Neekon Vafa , Vinod Vaikuntanathan

In this paper we consider the classical spherical perceptron problem. This problem and its variants have been studied in a great detail in a broad literature ranging from statistical physics and neural networks to computer science and pure…

Probability · Mathematics 2013-06-19 Mihailo Stojnic

Constraint Satisfaction Problems are ubiquitous in fields ranging from the physics of solids to artificial intelligence. In many cases, such systems undergo a transition when the ratio of constraints to variables reaches some value…

Statistical Mechanics · Physics 2025-03-25 Michael Winer , Aidan Herderschee

In the negative perceptron problem we are given $n$ data points $({\boldsymbol x}_i,y_i)$, where ${\boldsymbol x}_i$ is a $d$-dimensional vector and $y_i\in\{+1,-1\}$ is a binary label. The data are not linearly separable and hence we…

Machine Learning · Computer Science 2025-03-25 Andrea Montanari , Yiqiao Zhong , Kangjie Zhou

We study potential presence of statistical-computational gaps (SCG) in symmetric binary perceptrons (SBP) via a parametric utilization of \emph{fully lifted random duality theory} (fl-RDT) [96]. A structural change from decreasingly to…

Machine Learning · Statistics 2026-01-16 Mihailo Stojnic

We study the random binary symmetric perceptron problem, focusing on the behavior of rare high-margin solutions. While most solutions are isolated, we demonstrate that these rare solutions are part of clusters of extensive entropy,…

Probability · Mathematics 2024-07-22 Damien Barbier , Ahmed El Alaoui , Florent Krzakala , Lenka Zdeborová

A central challenge in machine learning is to distinguish genuine structure from chance correlations in high-dimensional data. In this work, we address this issue for the perceptron, a foundational model of neural computation. Specifically,…

Information Theory · Computer Science 2025-12-02 Yingying Xu , Masayuki Ohzeki , Yoshiyuki Kabashima

Consider the $n$-dimensional vector $y=X\be+\e$, where $\be \in \R^p$ has only $k$ nonzero entries and $\e \in \R^n$ is a Gaussian noise. This can be viewed as a linear system with sparsity constraints, corrupted by noise. We find a…

Information Theory · Computer Science 2009-10-13 Kamiar Rahnama Rad

In this paper, a continuous and non-convex promoting sparsity fraction function is studied in two sparse portfolio selection models with and without short-selling constraints. Firstly, we study the properties of the optimal solution to the…

Optimization and Control · Mathematics 2018-01-30 Angang Cui , Jigen Peng , Chengyi Zhang , Haiyang Li , Meng Wen

This thesis focus on the extension of the Parisi full replica symmetry breaking solution to the Ising spin glass on a random regular graph. We propose a new martingale approach, that overcomes the limits of the Parisi-M\'ezard cavity…

Statistical Mechanics · Physics 2019-11-05 Francesco Concetti

We present a simple and intuitive approximation for solving perturbation theory (PT) of small cosmic fluctuations. We consider only the spherically symmetric or monopole contribution to the PT integrals, which yields the exact result for…

Astrophysics · Physics 2009-10-30 P. Fosalba , E. Gaztanaga

In this article the framework for Parisi's spontaneous replica symmetry breaking is reviewed, and subsequently applied to the example of the statistical mechanical description of the storage properties of a McCulloch-Pitts neuron. The…

Disordered Systems and Neural Networks · Physics 2009-10-31 G. Gyorgyi

We investigate near the point of glass transition the expansion of the free energy corresponding to the generalized Sherrington--Kirkpatrick model with arbitrary diagonal operators U standing instead of Ising spins. We focus on the case…

Statistical Mechanics · Physics 2013-03-07 E. E. Tareyeva , T. I. Schelkacheva , N. M. Chtchelkatchev

In this paper we adapt the broken replica interpolation technique (developed by Francesco Guerra to deal with the Sherrington-Kirkpatrick model, namely a pairwise mean-field spin-glass whose couplings are i.i.d. standard Gaussian variables)…

Mathematical Physics · Physics 2020-06-02 Elena Agliari , Linda Albanese , Adriano Barra , Gabriele Ottaviani

An encryption of a signal ${\bf s}\in\mathbb{R^N}$ is a random mapping ${\bf s}\mapsto \textbf{y}=(y_1,\ldots,y_M)^T\in \mathbb{R}^M$ which can be corrupted by an additive noise. Given the Encryption Redundancy Parameter (ERP) $\mu=M/N\ge…

Disordered Systems and Neural Networks · Physics 2019-06-11 Yan V Fyodorov

We study the replica-symmetric saddle point equations for the Ising perceptron with Gaussian disorder and margin $\kappa\ge 0$. We prove that for each $\kappa\ge 0$ there is a critical capacity $\alpha_c(\kappa)=\frac{2}{\pi\,\mathbb…

Probability · Mathematics 2025-12-30 Shuta Nakajima

The weight space of the Ising perceptron in which a set of random patterns is stored is examined using the generating function of the partition function $\phi(n)=(1/N)\log [Z^n]$ as the dimension of the weight vector $N$ tends to infinity,…

Disordered Systems and Neural Networks · Physics 2015-05-14 Tomoyuki Obuchi , Yoshiyuki Kabashima

We consider the Ising perceptron with gaussian disorder, which is equivalent to the discrete cube $\{-1,+1\}^N$ intersected by $M$ random half-spaces. The perceptron's capacity is $\alpha_N \equiv M_N/N$ for the largest integer $M_N$ such…

Probability · Mathematics 2018-09-21 Jian Ding , Nike Sun

The symmetric binary perceptron ($\texttt{SBP}$) exhibits a dramatic statistical-to-computational gap: the densities at which known efficient algorithms find solutions are far below the threshold for the existence of solutions. Furthermore,…

Computational Complexity · Computer Science 2022-03-30 David Gamarnik , Eren C. Kızıldağ , Will Perkins , Changji Xu

We prove the existence of a shattered phase within the replica-symmetric phase of the pure spherical $p$-spin models for $p$ sufficiently large. In this phase, we construct a decomposition of the sphere into well-separated small clusters,…

Probability · Mathematics 2025-01-22 Ahmed El Alaoui , Andrea Montanari , Mark Sellke
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