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Related papers: Generalized R\'enyi statistics

200 papers

Despite the tremendous progress in the estimation of generative models, the development of tools for diagnosing their failures and assessing their performance has advanced at a much slower pace. Recent developments have investigated metrics…

Machine Learning · Computer Science 2020-06-09 Josip Djolonga , Mario Lucic , Marco Cuturi , Olivier Bachem , Olivier Bousquet , Sylvain Gelly

Many axiomatic definitions of entropy, such as the R\'enyi entropy, of a random variable are closely related to the $\ell_{\alpha}$-norm of its probability distribution. This study considers probability distributions on finite sets, and…

Information Theory · Computer Science 2016-05-06 Yuta Sakai , Ken-ichi Iwata

The results of the renormalization group are commonly advertised as the existence of power law singularities near critical points. The classic predictions are often violated and logarithmic and exponential corrections are treated on a…

Integrating the outputs of multiple classifiers via combiners or meta-learners has led to substantial improvements in several difficult pattern recognition problems. In the typical setting investigated till now, each classifier is trained…

Machine Learning · Computer Science 2007-05-23 Kagan Tumer , Joydeep Ghosh

Datasets with extreme observations and/or heavy-tailed error distributions are commonly encountered and should be analyzed with careful consideration of these features from a statistical perspective. Small deviations from an assumed model,…

Methodology · Statistics 2023-01-12 Meadhbh O'Neill , Kevin Burke

This paper investigates pooling strategies for tail index and extreme quantile estimation from heavy-tailed data. To fully exploit the information contained in several samples, we present general weighted pooled Hill estimators of the tail…

Statistics Theory · Mathematics 2021-11-08 Abdelaati Daouia , Simone A. Padoan , Gilles Stupfler

Quantum key distribution requires tight and reliable bounds on the secret key rate to ensure robust security. This is particularly so for the regime of finite block sizes, where the optimization of generalized R\'enyi entropic quantities is…

Quantum Physics · Physics 2026-04-09 Rebecca R. B. Chung , Nelly H. Y. Ng , Yu Cai

There are a number of mathematical formalisms of the term "outlier" in statistics, though there is no consensus on what the right notion ought to be. Accordingly, we try to give a consistent and robust definition for a specific type of…

Methodology · Statistics 2022-07-27 Ahmet Zahid Balcıoğlu , Oğuz Gürerk

Rare events play a key role in many applications and numerous algorithms have been proposed for estimating the probability of a rare event. However, relatively little is known on how to quantify the sensitivity of the probability with…

Probability · Mathematics 2019-02-06 Paul Dupuis , Markos A. Katsoulakis , Yannis Pantazis , Luc Rey-Bellet

We study tail estimation in Pareto-like settings for datasets with a high percentage of randomly right-censored data, and where some expert information on the tail index is available for the censored observations. This setting arises for…

Applications · Statistics 2019-11-13 Martin Bladt , Hansjoerg Albrecher , Jan Beirlant

We examine the following version of a classic combinatorial search problem introduced by R\'enyi: Given a finite set $X$ of $n$ elements we want to identify an unknown subset $Y \subset X$ of exactly $d$ elements by testing, by as few as…

Combinatorics · Mathematics 2015-09-02 Fabrício S. Benevides , Dániel Gerbner , Cory T. Palmer , Dominik K. Vu

We show how to control the generalization error of time series models wherein past values of the outcome are used to predict future values. The results are based on a generalization of standard i.i.d. concentration inequalities to dependent…

Machine Learning · Statistics 2017-05-24 Daniel J. McDonald , Cosma Rohilla Shalizi

Two key tasks in high-dimensional regularized regression are tuning the regularization strength for accurate predictions and estimating the out-of-sample risk. It is known that the standard approach -- $k$-fold cross-validation -- is…

Statistics Theory · Mathematics 2025-10-24 Kevin Luo , Yufan Li , Pragya Sur

Consider two batches of independent or interdependent exponentiated location-scale distributed heterogeneous random variables. This article investigates ordering results for the second-order statistics from these batches when a vector of…

Statistics Theory · Mathematics 2021-04-20 Sangita Das , Suchandan Kayal

In this note, we provide analytic expressions for the R\'enyi common information of orders in $(1,\infty)$ for the doubly symmetric binary source (DSBS). Until now, analytic expressions for the R\'enyi common information of all orders in…

Information Theory · Computer Science 2024-07-09 Lei Yu

For a fixed positive integer $\;k,\;$ limit laws of linearly normalized $\;k$-th upper order statistics are well known. In this article, a comprehensive study of tail behaviours of limit laws of normalized $k$-th upper order statistics…

Probability · Mathematics 2015-12-11 Sreenivasan Ravi , Mandagere Chandrashekhar Manohar

We obtain an uniform tail estimates for natural normed sums of independent random variables (r.v.) with regular varying tails of distributions. We give also many examples on order to show the exactness of offered estimates and discuss some…

Probability · Mathematics 2012-06-22 E. Ostrovsky , L. Sirota

Lower bounds for the R\'enyi entropies of sums of independent random variables taking values in cyclic groups of prime order under permutations are established. The main ingredients of our approach are extended rearrangement inequalities in…

Combinatorics · Mathematics 2021-10-20 Mokshay Madiman , Liyao Wang , Jae Oh Woo

The upper tail problem in a random graph asks to estimate the probability that the number of copies of some fixed subgraph in an Erd\H{o}s--R\'enyi random graph exceeds its expectation by some constant factor. There has been much exciting…

Combinatorics · Mathematics 2020-10-27 Yang P. Liu , Yufei Zhao

The log transformation is widely used in linear regression, mainly because coefficients are interpretable as proportional effects. Yet this practice has fundamental limitations, most notably that the log is undefined at zero, creating an…

Econometrics · Economics 2025-09-22 David Benatia , Christophe Bellégo , Louis Pape