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Related papers: Small ball estimates for quasi-norms

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We introduce a new framework for analyzing (Quasi-}Newton type methods applied to non-smooth optimization problems. The source of randomness comes from the evaluation of the (approximation) of the Hessian. We derive, using a variant of…

Optimization and Control · Mathematics 2025-03-05 Titus Pinta

In this article we study the small ball probabilities in $L_2$-norm for a family of finite-dimensional perturbations of Gaussian functions. We define three types of perturbations: non-critical, partially critical and critical; and derive…

Probability · Mathematics 2023-08-23 Yulia Petrova

There are many ways of establishing upper bounds on fluctuations of random variables, but there is no systematic approach for lower bounds. As a result, lower bounds are unknown in many important problems. This paper introduces a general…

Probability · Mathematics 2018-07-30 Sourav Chatterjee

This is basically a review of the field of Quasi-Monte Carlo intended for computational physicists and other potential users of quasi-random numbers. As such, much of the material is not new, but is presented here in a style hopefully more…

High Energy Physics - Phenomenology · Physics 2010-11-11 Fred James , Jiri Hoogland , Ronald Kleiss

The purpose of this note is to collect in one place a few results about simple random walk and Brownian motion which are often useful. These include standard results such as Beurling estimates, large deviation estimates, and a method for…

Probability · Mathematics 2007-05-23 Christian Benes

We derive an upper bound on the size of a ball such that the image of the ball under quadratic map is strongly convex and smooth. Our result is the best possible improvement of the analogous result by Polyak in the case of quadratic map. We…

Optimization and Control · Mathematics 2017-10-27 Anatoly Dymarsky

The adaptive quasi-likelihood analysis is developed for a degenerate diffusion process. Asymptotic normality and moment convergence are proved for the quasi-maximum likelihood estimators and quasi-Bayesian estimators, in the adaptive…

Statistics Theory · Mathematics 2024-06-10 Arnaud Gloter , Nakahiro Yoshida

We establish simultaneous approximation properties of weighted first-order Sobolev orthogonal projectors onto spaces of polynomials of bounded total degree in the Euclidean unit ball. The simultaneity is in the sense that we provide bounds…

Classical Analysis and ODEs · Mathematics 2023-08-21 Leonardo E. Figueroa

We estimate from below the expected Betti numbers of real hypersurfaces taken at random in a smooth real projective n-dimensional manifold. These random hypersurfaces are chosen in the linear system of a large d-th power of a real ample…

Symplectic Geometry · Mathematics 2017-05-17 Damien Gayet , Jean-Yves Welschinger

In this paper, we would like to derive three-ball inequalities and propagation of smallness for the complex second order elliptic equation with discontinuous Lipschitz coefficients. As an application of such estimates, we study the size…

Analysis of PDEs · Mathematics 2020-07-03 Elisa Francini , Sergio Vessella , Jenn-Nan Wang

An extension of the Gauss-Newton algorithm is proposed to find local minimizers of penalized nonlinear least squares problems, under generalized Lipschitz assumptions. Convergence results of local type are obtained, as well as an estimate…

Optimization and Control · Mathematics 2011-03-03 Saverio Salzo , Silvia Villa

We establish the convergences (with respect to the simulation time $t$; the number of particles $N$; the timestep $\gamma$) of a Moran/Fleming-Viot type particle scheme toward the quasi-stationary distribution of a diffusion on the…

Probability · Mathematics 2020-10-21 Lucas Journel , Pierre Monmarché

We show how random subspace methods can be adapted to estimating local projections with many controls. Random subspace methods have their roots in the machine learning literature and are implemented by averaging over regressions estimated…

Econometrics · Economics 2024-06-04 Viet Hoang Dinh , Didier Nibbering , Benjamin Wong

We propose and investigate a new estimation method for the parameters of models consisting of smooth density functions on the positive half axis. The procedure is based on a recently introduced characterization result for the respective…

Statistics Theory · Mathematics 2021-06-16 Steffen Betsch , Bruno Ebner , Bernhard Klar

In this article, we study the limit distribution of the least square estimator, properly normalized, from a regression model in which observations are assumed to be finite ($\alpha N$) and sampled under two different random times. Based on…

Statistics Theory · Mathematics 2020-12-17 Tania Roa , Soledad Torres , Ciprian tudor

We provide finite sample bounds on the Normal approximation to the law of the least squares estimator of the projection parameters normalized by the sandwich-based standard errors. Our results hold in the increasing dimension setting and…

Statistics Theory · Mathematics 2021-10-25 Arun Kumar Kuchibhotla , Alessandro Rinaldo , Larry Wasserman

We study the nonparametric estimators of the infinitesimal coefficients of the second-order jump-diffusion models. Under the mild conditions, we obtain the weak consistency and the asymptotic normalities of the estimators.

Statistics Theory · Mathematics 2017-07-07 Zheng-Yan Lin , Yu-Ping Song , Han-Chao Wang

Quasinormal modes describe the ringdown of compact objects deformed by small perturbations. In generic theories of gravity that extend General Relativity, the linearized dynamics of these perturbations is described by a system of coupled…

General Relativity and Quantum Cosmology · Physics 2023-10-04 Lam Hui , Alessandro Podo , Luca Santoni , Enrico Trincherini

We define Landau quasi-particles within the Gutzwiller variational theory, and derive their dispersion relation for general multi-band Hubbard models in the limit of large spatial dimensions D. Thereby we reproduce our previous calculations…

Strongly Correlated Electrons · Physics 2009-11-07 J. Buenemann , F. Gebhard , R. Thul

Let $X$ be a $d$-dimensional random vector and $X_\theta$ its projection onto the span of a set of orthonormal vectors $\{\theta_1,...,\theta_k\}$. Conditions on the distribution of $X$ are given such that if $\theta$ is chosen according to…

Probability · Mathematics 2011-02-16 Elizabeth Meckes