English
Related papers

Related papers: A thrust to trust minimum thrust

200 papers

It is shown that if the Euclidean path integral measure of a minimally coupled free quantum scalar field on a classical metric background is interpreted as probability of observing the field configuration given the background metric then…

Quantum Physics · Physics 2021-02-22 Can Gokler

A new variant of Newton's method for empirical risk minimization is studied, where at each iteration of the optimization algorithm, the gradient and Hessian of the objective function are replaced by robust estimators taken from existing…

Machine Learning · Statistics 2023-07-18 Eirini Ioannou , Muni Sreenivas Pydi , Po-Ling Loh

The vast majority of scientific community believes that P!=NP, with countless supporting arguments. The number of people who believe otherwise probably amounts to as few as those opposing the 2nd Law of Thermodynamics. But isn't nature…

Data Structures and Algorithms · Computer Science 2011-04-12 Eduardo Hwang

In the context of stability of the extremes of a random variable X with respect to a positive integer valued random variable N we discuss the cases (i) X is exponential (ii) non-geometric laws for N (iii) identifying N for the stability of…

Probability · Mathematics 2007-06-13 S. Satheesh , N. U. Nair

In the presence of model risk, it is well-established to replace classical expected values by worst-case expectations over all models within a fixed radius from a given reference model. This is the "robustness" approach. We show that…

Risk Management · Quantitative Finance 2015-10-07 Thomas Kruse , Judith C. Schneider , Nikolaus Schweizer

We propose a novel clustering method that is based on physical intuition derived from quantum mechanics. Starting with given data points, we construct a scale-space probability function. Viewing the latter as the lowest eigenstate of a…

Data Analysis, Statistics and Probability · Physics 2007-05-23 David Horn , Assaf Gottlieb

We study the problem of certifying the robustness of Bayesian neural networks (BNNs) to adversarial input perturbations. Given a compact set of input points $T \subseteq \mathbb{R}^m$ and a set of output points $S \subseteq \mathbb{R}^n$,…

Machine Learning · Computer Science 2023-06-26 Matthew Wicker , Andrea Patane , Luca Laurenti , Marta Kwiatkowska

The statistical problem of estimating the effective dimension-reduction (EDR) subspace in the multi-index regression model with deterministic design and additive noise is considered. A new procedure for recovering the directions of the EDR…

Statistics Theory · Mathematics 2007-06-13 Arnak Dalalyan , Anatoly Juditsky , Vladimir Spokoiny

We prove an estimate on the smallest singular value of a multiplicatively and additively deformed random rectangular matrix. Suppose $n\le N \le M \le \Lambda N$ for some constant $\Lambda \ge 1$. Let $X$ be an $M\times n$ random matrix…

Probability · Mathematics 2018-10-17 Fan Yang

To determine whether an $n\times n$-matrix has rank at most $r$ it suffices to check that the $(r+1)\times (r+1)$-minors have rank at most $r$. In other words, to describe the set of $n\times n$-matrices with the property of having rank at…

Algebraic Geometry · Mathematics 2024-06-14 Andreas Blatter

Let $n>m$, and let $A$ be an $(m\times n)$-matrix of full rank. Then obviously the estimate $\|Ax\|\leq\|A\|\|x\|$ holds for the euclidean norm of $x$ and $Ax$ and the spectral norm as the assigned matrix norm. We study the sets of all $x$…

Rings and Algebras · Mathematics 2022-03-16 Harry Yserentant

We consider a data-driven robust hypothesis test where the optimal test will minimize the worst-case performance regarding distributions that are close to the empirical distributions with respect to the Wasserstein distance. This leads to a…

Statistics Theory · Mathematics 2021-06-01 Liyan Xie , Rui Gao , Yao Xie

Scientific explanation often requires inferring maximally predictive features from a given data set. Unfortunately, the collection of minimal maximally predictive features for most stochastic processes is uncountably infinite. In such…

Statistical Mechanics · Physics 2017-05-31 Sarah E. Marzen , James P. Crutchfield

While Bayesian neural networks (BNNs) have drawn increasing attention, their posterior inference remains challenging, due to the high-dimensional and over-parameterized nature. To address this issue, several highly flexible and scalable…

Machine Learning · Statistics 2019-05-10 Ziyu Wang , Tongzheng Ren , Jun Zhu , Bo Zhang

We consider a variant of bin packing called multiple-choice vector bin packing. In this problem we are given a set of items, where each item can be selected in one of several $D$-dimensional incarnations. We are also given $T$ bin types,…

Data Structures and Algorithms · Computer Science 2015-05-14 Boaz Patt-Shamir , Dror Rawitz

The proof of the theorem, which states that the Euclidean metric on the set of random points in an $n$-dimensional Euclidean space with the distribution of a special class, converges in probability in the limit $n\rightarrow\infty$ to the…

Mathematical Physics · Physics 2014-04-22 Alexander P. Zubarev

We propose a new algorithm for the solution of the robust multiple-load topology optimization problem. The algorithm can be applied to any type of problem, e.g., truss topology, variable thickness sheet or free material optimization. We…

Optimization and Control · Mathematics 2013-07-30 Michal Kocvara

The present paper attempts to address a discussion on mathematical grounds of a model to associate the generalized version of the CLT and the $N$-body problem related to the calculation of the force on a single star or particle due to the…

Mathematical Physics · Physics 2019-07-24 A. D. Figueiredo , T. M. da Rocha Filho , M. A. Amato

For a given external loading on a structure we consider the optimal stresses. Ignoring the material properties the structure may have, we look for the distribution of internal forces or stresses that is in equilibrium with the external…

Computational Physics · Physics 2007-05-23 Reuven Segev , Gal deBotton

We study the minimization of the expected costs under stochastic constraint at the terminal time. The first and the main result says that for a power type of costs, the value function is the minimal positive solution of a second order…

Probability · Mathematics 2020-01-28 Yan Dolinsky , Benjamin Gottesman , Ori Gurel-Gurevich
‹ Prev 1 3 4 5 6 7 10 Next ›