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We design and analyze an algorithm for first-order stochastic optimization of a large class of functions on $\mathbb{R}^d$. In particular, we consider the \emph{variationally coherent} functions which can be convex or non-convex. The…

Optimization and Control · Mathematics 2021-02-02 Francesco Orabona , Dávid Pál

Maximizing the likelihood has been widely used for estimating the unknown covariance parameters of spatial Gaussian processes. However, evaluating and optimizing the likelihood function can be computationally intractable, particularly for…

Statistics Theory · Mathematics 2019-07-16 Hossein Keshavarz , XuanLong Nguyen , Clayton Scott

Standard regression approaches assume that some finite number of the response distribution characteristics, such as location and scale, change as a (parametric or nonparametric) function of predictors. However, it is not always appropriate…

Methodology · Statistics 2020-07-14 Fernand A. Quintana , Peter Mueller , Alejandro Jara , Steven N. MacEachern

Data can be assumed to be continuous functions defined on an infinite-dimensional space for many phenomena. However, the infinite-dimensional data might be driven by a small number of latent variables. Hence, factor models are relevant for…

Methodology · Statistics 2022-05-18 Israel Martínez-Hernández , Jesús Gonzalo , Graciela González-Farías

Change point tests for abrupt changes in the mean of functional data, i.e., random elements in infinite-dimensional Hilbert spaces, are either based on dimension reduction techniques, e.g., based on principal components, or directly based…

Statistics Theory · Mathematics 2026-01-23 Claudia Kirch , Hedvika Ranošová , Martin Wendler

Recently, Portelli et al (2003) have semi-numerically obtained a functional form of the probability distribution of fluctuations in the total energy flow in a model for fluid turbulence. This follows earlier work suggesting that…

Statistical Mechanics · Physics 2007-05-23 S. C. Chapman , G. Rowlands , N. W. Watkins

We introduce a general, flexible, parametric survival modelling framework which encompasses key shapes of hazard function (constant, increasing, decreasing, up-then-down, down-then-up), various common survival distributions (log-logistic,…

Methodology · Statistics 2019-01-11 Kevin Burke , M. C. Jones , Angela Noufaily

We consider a stochastic logistic growth model involving both birth and death rates in the drift and diffusion coefficients for which extinction eventually occurs almost surely. The associated complete Fokker-Planck equation describing the…

Statistics Theory · Mathematics 2013-07-09 Fabien Campillo , Marc Joannides , Irène Larramendy-Valverde

In systems belonging to the universality class of the random field Ising model, the standard hyperscaling relation between critical exponents does not hold, but is replaced by a modified hyperscaling relation. As a result, standard…

Statistical Mechanics · Physics 2010-12-01 R. L. C. Vink , T. Fischer , K. Binder

We study the universal scaling behavior of the entanglement entropy of critical theories in $2+1$ dimensions. We specially consider two fermionic scale-invariant models, free massless Dirac fermions and a model of fermions with quadratic…

Strongly Correlated Electrons · Physics 2015-02-24 Xiao Chen , Gil Young Cho , Thomas Faulkner , Eduardo Fradkin

Within the scaling laws paradigm, which underpins the training of large neural networks like ChatGPT and Llama, we consider a supervised regression setting and establish the existance of a strong form of the model collapse phenomenon, a…

Machine Learning · Computer Science 2024-10-10 Elvis Dohmatob , Yunzhen Feng , Arjun Subramonian , Julia Kempe

Based on discrete element method simulations, we propose a new form of the constitution equation for granular flows independent of packing fraction. Rescaling the stress ratio $\mu$ by a power of dimensionless temperature $\Theta$ makes the…

Soft Condensed Matter · Physics 2020-08-26 Seongmin Kim , Ken Kamrin

We investigate cosmological models described by a scalar field with an exponential potential, and apply the stochastic formalism, which allows us to study how quantum field fluctuations give rise to stochastic noise. This modifies the…

General Relativity and Quantum Cosmology · Physics 2020-01-24 Tays Miranda , Emmanuel Frion , David Wands

Recently, a novel model to describe ordering in systems comprising agents which, although matching in their binarity (i.e., maintaining the iconic Ising features of ``+'' or ``-'', ``up'' or ``down'', ``yes'' or ``no''), still differing in…

Statistical Mechanics · Physics 2024-09-25 M. Krasnytska

The Polyak stepsize for Gradient Descent is known for its fast convergence but requires prior knowledge of the optimal functional value, which is often unavailable in practice. In this paper, we propose a parameter-free approach that…

Optimization and Control · Mathematics 2025-08-26 Farshed Abdukhakimov , Cuong Anh Pham , Samuel Horváth , Martin Takáč , Slavomır Hanzely

The Maximal Update Parametrization ($\mu$P) aims to make the optimal hyperparameters (HPs) of a model independent of its size, allowing them to be swept using a cheap proxy model rather than the full-size target model. We present a new…

We analyze the quantum phase transition between a semimetal and a superfluid in a model of attractively interacting fermions with a linear dispersion. The quantum critical properties of this model cannot be treated by the Hertz-Millis…

Strongly Correlated Electrons · Physics 2011-06-06 P. Strack , S. Takei , W. Metzner

The scaling behavior of the order parameter at the chiral phase transition, the so-called magnetic equation of state, of strongly interacting matter is studied within effective models. We explore universal and nonuniversal structures near…

High Energy Physics - Phenomenology · Physics 2017-02-01 Gabor Andras Almasi , Wojciech Tarnowski , Bengt Friman , Krzysztof Redlich

Scale free dynamics are observed in a variety of physical and biological systems. These include neural activity in which evidence for scale freeness has been reported using a range of imaging modalities. Here, we derive the ways in which…

Functional graphical models have undergone extensive development during the recent years, leading to a variety models such as the functional Gaussian graphical model, the functional copula Gaussian graphical model, the functional Bayesian…

Methodology · Statistics 2026-01-23 Kyongwon Kim , Bing Li