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For functions of independent random variables, various upper and lower variance bounds are revisited in diverse settings. These are then specialized to the Bernoulli, Gaussian, infinitely divisible cases and to Banach space valued random…

Probability · Mathematics 2024-10-16 Clément Deslandes , Christian Houdré

We consider a process $Z$ on the real line composed from a L\'evy process and its exponentially tilted version killed with arbitrary rates and give an expression for the joint law of $Z$ seen from its supremum, the supremum $\overline Z$…

Probability · Mathematics 2014-05-15 Sebastian Engelke , Jevgenijs Ivanovs

The task of analyzing extreme events with censoring effects is considered under a framework allowing for random covariate information. A wide class of estimators that can be cast as product-limit integrals is considered, for when the…

Statistics Theory · Mathematics 2024-08-14 Martin Bladt , Christoffer Øhlenschlæger

In many areas of engineering and sciences, decision rules and control strategies are usually designed based on nominal values of relevant system parameters. To ensure that a control strategy or decision rule will work properly when the…

Probability · Mathematics 2020-06-16 Xinjia Chen

Statistical inference from data is a foundational task in science. Recently, it has received growing attention for its central role in inference systems of primary interest in data sciences and machine learning. However, the understanding…

Statistical Mechanics · Physics 2022-10-12 Hyun Keun Lee , Chulan Kwon , Yong Woon Kim

By using Beta Dirichlet series and then Eisenstein series we ca represent primes with first a good approximation and an exact expression. This can be done with arbitrary prime (up to 10^101).

Number Theory · Mathematics 2023-05-17 Simon Plouffe

We consider list versions of sparse approximation problems, where unlike the existing results in sparse approximation that consider situations with unique solutions, we are interested in multiple solutions. We introduce these problems and…

Information Theory · Computer Science 2014-08-12 Mahmoud Abo Khamis , Anna C. Gilbert , Hung Q. Ngo , Atri Rudra

Research in natural language processing proceeds, in part, by demonstrating that new models achieve superior performance (e.g., accuracy) on held-out test data, compared to previous results. In this paper, we demonstrate that test-set…

Machine Learning · Computer Science 2019-09-09 Jesse Dodge , Suchin Gururangan , Dallas Card , Roy Schwartz , Noah A. Smith

We consider upper exponential bounds for the probability of the event that an absolute deviation of sample mean from mathematical expectation p is bigger comparing with some ordered level epsilon. These bounds include 2 coefficients {alpha,…

Probability · Mathematics 2010-04-13 Vladimir Nikulin

Synchronization of finite spike sequences is the way two brain regions compare their content and extract the most suitable sequence. This is the core of the linguistic comparison between a word and a previous one retrieved by memory.…

Neurons and Cognition · Quantitative Biology 2018-07-10 F. T. Arecchi

In applications it is common that the exact form of a conditional expectation is unknown and having flexible functional forms can lead to improvements. Series method offers that by approximating the unknown function based on $k$ basis…

Methodology · Statistics 2017-10-05 Alexandre Belloni , Victor Chernozhukov , Denis Chetverikov , Kengo Kato

We consider a stochastic optimization problem involving two random variables: a context variable $X$ and a dependent variable $Y$. The objective is to minimize the expected value of a nonlinear loss functional applied to the conditional…

Optimization and Control · Mathematics 2026-03-16 Noel Smith , Andrzej Ruszczynski

In this paper we consider the problem of estimating the parameters of a Poisson arrival process where the rate function is assumed to lie in the span of a known basis. Our goal is to estimate the basis expansions coefficients given a…

Information Theory · Computer Science 2018-12-24 Michael G. Moore , Mark A. Davenport

We view sequential design as a model selection problem to determine which new observation is expected to be the most informative, given the existing set of observations. For estimating a probability distribution on a bounded interval, we…

Methodology · Statistics 2018-07-19 Madhurima Nath , Stephen Eubank

Superstatistics describes nonequilibrium steady states as superpositions of canonical ensembles with a probability distribution of temperatures. Rather than assume a certain distribution of temperature, recently [J. Phys. A: Math. Theor.…

Statistical Mechanics · Physics 2020-10-28 Sergio Davis

Generalized linear models play an essential role in a wide variety of statistical applications. This paper discusses an approximation of the likelihood in these models that can greatly facilitate computation. The basic idea is to replace a…

Methodology · Statistics 2013-05-27 Alexandro D. Ramirez , Liam Paninski

A characterization of the exponential distribution based on equidistribution conditions for maxima of random samples with consecutive sizes n-1 and n for an arbitrary and fixed n>2 is proved. This solves an open problem stated recently in…

Probability · Mathematics 2015-02-24 Santanu Chakraborty , George P. Yanev

The syntactic structure of a sentence is often represented using syntactic dependency trees. The sum of the distances between syntactically related words has been in the limelight for the past decades. Research on dependency distances led…

Computation and Language · Computer Science 2023-10-16 Lluís Alemany-Puig , Ramon Ferrer-i-Cancho

This paper has two purposes. One is to demonstrate contextuality analysis of systems of epistemic random variables. The other is to evaluate the performance of a new, hierarchical version of the measure of (non)contextuality introduced in…

Neurons and Cognition · Quantitative Biology 2020-09-04 Víctor H. Cervantes , Ehtibar N. Dzhafarov

Consider an M/M/$s$ queue with the additional feature that the arrival rate is a random variable of which only the mean, variance, and range are known. Using semi-infinite linear programming and duality theory for moment problems, we…