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This paper proposes a stochastic variant of a classic algorithm---the cubic-regularized Newton method [Nesterov and Polyak 2006]. The proposed algorithm efficiently escapes saddle points and finds approximate local minima for general…

Machine Learning · Computer Science 2017-12-07 Nilesh Tripuraneni , Mitchell Stern , Chi Jin , Jeffrey Regier , Michael I. Jordan

This paper is concerned with the convergence rate of the solutions of nonlinear switched systems. We first consider a switched system which is asymptotically stable for a class of inputs but not for all inputs. We show that solutions…

Optimization and Control · Mathematics 2015-11-06 Philippe Jouan , Saïd Naciri

This paper considers the posterior contraction of non-parametric Bayesian inference on non-homogeneous Poisson processes. We consider the quality of inference on a rate function $\lambda$, given non-identically distributed realisations,…

Statistics Theory · Mathematics 2019-06-26 James A. Grant , David S. Leslie

Let $\beta>0$ and consider an $n$-point process $\lambda_1, \lambda_2,..., \lambda_n$ from Hermite $\beta$ ensemble on the real line $\mathbb{R}$. Dumitriu and Edelman discovered a tri-diagonal matrix model and established the global Wigner…

Probability · Mathematics 2011-04-19 Zhigang Bao , Zhonggen Su

A novel IV estimation method, that we term Locally Trimmed LS (LTLS), is developed which yields estimators with (mixed) Gaussian limit distributions in situations where the data may be weakly or strongly persistent. In particular, we allow…

Econometrics · Economics 2020-06-24 Zhishui Hu , Ioannis Kasparis , Qiying Wang

We study nonparametric Bayesian inference with location mixtures of the Laplace density and a Dirichlet process prior on the mixing distribution. We derive a contraction rate of the corresponding posterior distribution, both for the mixing…

Statistics Theory · Mathematics 2016-03-10 Fengnan Gao , Aad van der Vaart

In this paper we study the local times of vector-valued Gaussian fields that are `diagonally operator-self-similar' and whose increments are stationary. Denoting the local time of such a Gaussian field around the spatial origin and over the…

Probability · Mathematics 2019-10-15 Kamran Kalbasi , Thomas S. Mountford

Many data-fitting applications require the solution of an optimization problem involving a sum of large number of functions of high dimensional parameter. Here, we consider the problem of minimizing a sum of $n$ functions over a convex…

Optimization and Control · Mathematics 2016-02-29 Farbod Roosta-Khorasani , Michael W. Mahoney

Consider a class of null-recurrent randomly biased walks on a super-critical Gaton-Watson tree. We obtain the rates of convergence of the local times and the quenched local probability for the biased walk in the sub-diffusive case. These…

Probability · Mathematics 2019-01-03 Yueyun Hu

These notes provide an introduction to the local semicircle law from random matrix theory, as well as some of its applications. We focus on Wigner matrices, Hermitian random matrices with independent upper-triangular entries with zero…

Probability · Mathematics 2018-09-11 Florent Benaych-Georges , Antti Knowles

Bollerslev et al. (2006) study the cross-covariances for squared returns under the Heston (1993) stochastic volatility model. In order to obtain these cross-covariances the authors use an incorrect expression for the distribution of the…

Statistical Finance · Quantitative Finance 2009-02-05 Amparo Baillo

This work develops non-asymptotic theory for estimation of the long-run variance matrix and its inverse, the so-called precision matrix, for high-dimensional time series under general assumptions on the dependence structure including…

Statistics Theory · Mathematics 2023-01-02 Changryong Baek , Marie-Christine Düker , Vladas Pipiras

We propose a stochastic variance-reduced cubic regularized Newton method for non-convex optimization. At the core of our algorithm is a novel semi-stochastic gradient along with a semi-stochastic Hessian, which are specifically designed for…

Machine Learning · Computer Science 2018-02-14 Dongruo Zhou , Pan Xu , Quanquan Gu

We propose a nonperturbative scheme for the calculation of thermal damping-rates using exact renormalization group (RG)-equations. Special emphasis is put on the thermal RG where first results for the rate were given in M. Pietroni, Phys.…

High Energy Physics - Phenomenology · Physics 2009-10-31 Bastian Bergerhoff , Juergen Reingruber

In this paper, we establish explicit convergence rates for the stochastic smooth approximations of infimal convolutions introduced and developed in \cite{MR4581306,MR4923371}. In particular, we quantify the convergence of the associated…

Optimization and Control · Mathematics 2026-02-23 Diego Morales , Pedro Pérez-Aros , Emilio Vilches

The theory of Fourier integral operators is surveyed, with an emphasis on local smoothing estimates and their applications. After reviewing the classical background, we describe some recent work of the authors which established sharp local…

Analysis of PDEs · Mathematics 2019-09-06 David Beltran , Jonathan Hickman , Christopher D. Sogge

In this paper escape rates and local escape rates for special flows are sudied. In a general context the first result is that the escape rate depends monotonically on the ceiling function and fulfills certain scaling, invariance, and…

Dynamical Systems · Mathematics 2019-05-01 Fabian Dreher , Marc Kesseböhmer

We study local asymptotic properties of likelihood ratios of certain Heston models. We distinguish three cases: subcritical, critical and supercritical models. For the drift parameters, local asymptotic normality is proved in the…

Statistics Theory · Mathematics 2019-10-17 János Marcell Benke , Gyula Pap

We discuss the probabilistic properties of the variation based third and fourth moments of financial returns as estimators of the actual moments of the return distributions. The moment variations are defined under non-parametric assumptions…

Statistical Finance · Quantitative Finance 2019-08-15 Kyungsub Lee

We develop a local version of Huisken-Stampacchia iteration, using it to obtain local versions of a host of important sharp curvature pinching estimates for mean curvature flow. The local estimates we obtain do not depend on the quality of…

Differential Geometry · Mathematics 2021-04-01 Mat Langford
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