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We study a generic class of \emph{random optimization problems} (rops) and their typical behavior. The foundational aspects of the random duality theory (RDT), associated with rops, were discussed in \cite{StojnicRegRndDlt10}, where it was…

Probability · Mathematics 2023-12-04 Mihailo Stojnic

We study algorithmic aspects of finding $n$-dimensional \emph{positive} and \emph{negative} Hopfield ($\pm$Hop) model ground state free energies. This corresponds to classical maximization of random positive/negative semi-definite quadratic…

Disordered Systems and Neural Networks · Physics 2025-07-31 Mihailo Stojnic

We consider the classical \emph{spherical} perceptrons and study their capacities. The famous zero-threshold case was solved in the sixties of the last century (see, \cite{Wendel62,Winder,Cover65}) through the high-dimensional combinatorial…

Machine Learning · Statistics 2023-12-29 Mihailo Stojnic

We study the statistical capacity of the classical binary perceptrons with general thresholds $\kappa$. After recognizing the connection between the capacity and the bilinearly indexed (bli) random processes, we utilize a recent progress in…

Probability · Mathematics 2023-12-04 Mihailo Stojnic

In this paper we look at a class of random optimization problems that arise in the forms typically known in statistical physics as Little models. In \cite{BruParRit92} the Little models were studied by means of the well known tool from the…

Optimization and Control · Mathematics 2013-06-19 Mihailo Stojnic

An exact mapping is established between the $c\geq25$ Liouville field theory (LFT) and the Gibbs measure statistics of a thermal particle in a 2D Gaussian Free Field plus a logarithmic confining potential. The probability distribution of…

Statistical Mechanics · Physics 2017-06-16 Xiangyu Cao , Pierre Le Doussal , Alberto Rosso , Raoul Santachiara

In our recent work \cite{StojnicHopBnds10} we looked at a class of random optimization problems that arise in the forms typically known as Hopfield models. We viewed two scenarios which we termed as the positive Hopfield form and the…

Optimization and Control · Mathematics 2013-06-19 Mihailo Stojnic

Our companion paper \cite{Stojnicnflgscompyx23} introduced a very powerful \emph{fully lifted} (fl) statistical interpolating/comparison mechanism for bilinearly indexed random processes. Here, we present a particular realization of such fl…

Probability · Mathematics 2023-12-01 Mihailo Stojnic

We consider ground state energies (GSE) of multipartite $p$-spin models. Relying on partially lifted random duality theory (pl RDT) concepts we introduce an analytical mechanism that produces easy to compute lower and upper GSE bounds for…

Probability · Mathematics 2025-09-09 Mihailo Stojnic

We present the first mathematical analysis of stochastic density functional theory (DFT) in the context of the Hartree approximation. We motivate our analysis via the notion of nearly-optimal or $\tilde{O}(n)$ scaling with respect to the…

Numerical Analysis · Mathematics 2025-06-03 Yuhang Cai , Michael Lindsey

We analyze the properties of the quasiparticle excitations of metallic antiferromagnetic states in a strongly correlated electron system. The study is based on dynamical mean field theory (DMFT) for the infinite dimensional Hubbard model…

Strongly Correlated Electrons · Physics 2009-11-13 J. Bauer , A. C. Hewson

A powerful statistical interpolating concept, which we call \emph{fully lifted} (fl), is introduced and presented while establishing a connection between bilinearly indexed random processes and their corresponding fully decoupled (linearly…

Probability · Mathematics 2023-12-01 Mihailo Stojnic

Inequalities are key tools to prove FDR control of a multiple test. The present paper studies upper and lower bounds for the FDR under various dependence structures of p-values, namely independence, reverse martingale dependence and…

Statistics Theory · Mathematics 2015-02-18 Philipp Heesen , Arnold Janssen

We study the Hopfield model where the ratio $\alpha$ of patterns to sites grows large. We prove that the free energy with inverse temperature $\beta$ and external field $B$ behaves like $\beta\sqrt\alpha+\gamma$, where $\gamma$ is the…

Probability · Mathematics 2012-10-15 James Y. Zhao

The generalized linear models (GLM) have been widely used in practice to model non-Gaussian response variables. When the number of explanatory features is relatively large, scientific researchers are of interest to perform controlled…

Methodology · Statistics 2020-07-03 Chenguang Dai , Buyu Lin , Xin Xing , Jun S. Liu

The solution of complex many-body lattice models can often be found by defining an energy functional of the relevant density of the problem. For instance, in the case of the Hubbard model the spin-resolved site occupation is enough to…

Strongly Correlated Electrons · Physics 2019-02-20 James Nelson , Rajarshi Tiwari , Stefano Sanvito

Here, we investigate the fractal-lattice Hubbard model using various numerical methods: exact diagonalization, the self-consistent diagonalization of a (mean-field) Hartree-Fock Hamiltonian and state-of-the-art Auxiliary-Field Quantum Monte…

Strongly Correlated Electrons · Physics 2024-09-18 Monica Conte , Vinicius Zampronio , Malte Röntgen , Cristiane Morais Smith

The second-order reduced density matrix method (the RDM method) has performed well in determining energies and properties of atomic and molecular systems, achieving coupled-cluster singles and doubles with perturbative triples (CC SD(T))…

Strongly Correlated Electrons · Physics 2012-07-23 James S. M. Anderson , Maho Nakata , Ryo Igarashi , Katsuki Fujisawa , Makoto Yamashita

We propose a modification of the cost function of the Hopfield model whose salient features shine in its Taylor expansion and result in more than pairwise interactions with alternate signs, suggesting a unified framework for handling both…

Disordered Systems and Neural Networks · Physics 2018-01-08 Adriano Barra , Matteo Beccaria , Alberto Fachechi

To explore the relation between network structure and function, we studied the computational performance of Hopfield-type attractor neural nets with regular lattice, random, small-world and scale-free topologies. The random net is the most…

Disordered Systems and Neural Networks · Physics 2009-11-10 Patrick N. Mcgraw , Michael Menzinger
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