English
Related papers

Related papers: Measuring the influence of the k-th largest variab…

200 papers

The advent of explicit Dirac-Born-Infeld (DBI) inflationary models within string theory has drawn renewed interest to the cosmological role of unusual scalar field dynamics, usually referred to as k-inflation. In this situation, the…

Astrophysics · Physics 2009-01-07 Larissa Lorenz , Jerome Martin , Christophe Ringeval

The two most used citation impact indicators in the assessment of scientific journals are, nowadays, the impact factor and the h-index. However, both indicators are not field normalized (vary heavily depending on the scientific category)…

Digital Libraries · Computer Science 2015-10-14 Sara M. Gonzalez-Betancor , Pablo Dorta-Gonzalez

The Fourier coefficients F(t) of a function f on a compact symmetric space U/K are given by integration of f against matrix coefficients of irreducible representations of U. The coefficients depend on a spectral parameter t, which…

Representation Theory · Mathematics 2010-01-24 Gestur Olafsson , Henrik Schlichtkrull

We develop a new technique for proving concentration inequalities which relate between the variance and influences of Boolean functions. Using this technique, we 1. Settle a conjecture of Talagrand [Tal97] proving that $$\int_{\left\{…

Probability · Mathematics 2020-03-13 Ronen Eldan , Renan Gross

Here we introduce a fractional notion of $k$-dimensional measure, $0\leq k<n$, that depends on a parameter $\sigma$ that lies between $0$ and $1$. When $k=n-1$ this coincides with the fractional notions of area and perimeter, and when $k=1$…

Classical Analysis and ODEs · Mathematics 2023-03-22 Cornelia Mihaila , Brian Seguin

The h-index is a popular bibliometric indicator for assessing individual scientists. We criticize the h-index from a theoretical point of view. We argue that for the purpose of measuring the overall scientific impact of a scientist (or some…

Digital Libraries · Computer Science 2011-08-22 Ludo Waltman , Nees Jan van Eck

Factor importance measures the impact of each feature on output prediction accuracy. Many existing works focus on the model-based importance, but an important feature in one learning algorithm may hold little significance in another model.…

Methodology · Statistics 2025-06-24 Chaofan Huang , V. Roshan Joseph

In this paper, we develop a qualitative theory of influence diagrams that can be used to model and solve sequential decision making tasks when only qualitative (or imprecise) information is available. Our approach is based on an…

Artificial Intelligence · Computer Science 2012-02-20 Radu Marinescu , Nic Wilson

Influence functions approximate how removing a training example changes a quantity of interest, called the target function, such as a held-out loss. To estimate the influence of a group of examples, the standard practice is to sum the…

Machine Learning · Computer Science 2026-05-18 Jaeseung Heo , Kyeongheung Yun , Youngbin Choi , Sehyun Hwang , Jungseul Ok , Dongwoo Kim

In the first part of this paper we establish, in terms of so called k-tangential sets, a kind of optimal estimate for the size and structure of the set of non-differentiability of Lipshitz functions with one-sided directional derivatives.…

Classical Analysis and ODEs · Mathematics 2013-05-13 Hannes Luiro

The distribution of the sum of r-th power of standard normal random variables is a generalization of the chi-squared distribution. In this paper, we represent the probability density function of the random variable by an one-dimensional…

Classical Analysis and ODEs · Mathematics 2018-06-25 Tamio Koyama

In this note we introduce a generalized formula for Cohen's $d$ under the presence of additional independent variables, providing a measure for the size of a possible effect concerning the location difference of a variable in two groups.…

Applications · Statistics 2022-10-25 Jürgen Groß , Annette Möller

In order to advance academic research, it is important to assess and evaluate the academic influence of researchers and the findings they produce. Citation metrics are universally used methods to evaluate researchers. Amongst the several…

Digital Libraries · Computer Science 2023-05-18 Aashay Singhal , Kamalakar Karlapalem

We prove an invariance principle for functions on a slice of the Boolean cube, which is the set of all vectors {0,1}^n with Hamming weight k. Our invariance principle shows that a low-degree, low-influence function has similar distributions…

Probability · Mathematics 2016-02-23 Yuval Filmus , Guy Kindler , Elchanan Mossel , Karl Wimmer

We introduce a notion of "effective dimension" of a statistical model based on the number of cubes of size $1/\sqrt{n}$ needed to cover the model space when endowed with the Fisher Information Matrix as metric, $n$ being the number of…

Machine Learning · Statistics 2020-01-30 Oksana Berezniuk , Alessio Figalli , Raffaele Ghigliazza , Kharen Musaelian

In adaptive importance sampling, and other contexts, we have $K>1$ unbiased and uncorrelated estimates $\hat\mu_k$ of a common quantity $\mu$. The optimal unbiased linear combination weights them inversely to their variances but those…

Statistics Theory · Mathematics 2019-04-01 Art B. Owen , Yi Zhou

We study the statistics of citations made to the top ranked indexed journals for Science and Social Science databases in the Journal Citation Reports using different measures. Total annual citation and impact factor, as well as a third…

Digital Libraries · Computer Science 2014-03-10 Abdul Khaleque , Arnab Chatterjee , Parongama Sen

For a rational function f we consider the norm of the derivative with respect to the spherical metric and denote by K(f) the supremum of this norm. We give estimates of this quantity K(f) both for an individual function and for sequences of…

Dynamical Systems · Mathematics 2015-12-18 Matthew Barrett , Alexandre Eremenko

This article studies statistical estimation of $\pi$ based on the fact that the ratio of the volumes of a $d$-dimensional hypersphere and a $d$-dimensional hypercube is a certain function of $\pi$, and the function depends on the dimension…

Other Statistics · Statistics 2025-10-29 Syon Bhattacharjee , Subhra Sankar Dhar

When two variables are related by a known function, the coefficient of determination (denoted $R^2$) measures the proportion of the total variance in the observations that is explained by that function. This quantifies the strength of the…

Applications · Statistics 2013-03-11 Ben Murrell , Daniel Murrell , Hugh Murrell
‹ Prev 1 3 4 5 6 7 10 Next ›