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In this article, we construct semiparametrically efficient estimators of linear functionals of a probability measure in the presence of side information using an easy empirical likelihood approach. We use estimated constraint functions and…

Methodology · Statistics 2023-03-01 Shan Wang , Hanxiang Peng

Consider random matrices $A$, of dimension $m\times (m+n)$, drawn from an ensemble with probability density $f(\rmtr AA^\dagger)$, with $f(x)$ a given appropriate function. Break $A = (B,X)$ into an $m\times m$ block $B$ and the…

Probability · Mathematics 2007-06-13 Joshua Feinberg

Let $a_1, \dots, a_n \in \mathbb{R}$ satisfy $\sum_i a_i^2 = 1$, and let $\varepsilon_1, \ldots, \varepsilon_n$ be uniformly random $\pm 1$ signs and $X = \sum_{i=1}^{n} a_i \varepsilon_i$. It is conjectured that $X = \sum_{i=1}^{n} a_i…

Combinatorics · Mathematics 2022-08-01 Vojtěch Dvořák , Ohad Klein

Advances in precision medicine increasingly drive methodological innovation in health research. A key development is the use of personalized prediction models (PPMs), which are fit using a similar subpopulation tailored to a specific index…

Methodology · Statistics 2026-01-30 Tatiana Krikella , Joel A. Dubin

We study the fundamental task of estimating the median of an underlying distribution from a finite number of samples, under pure differential privacy constraints. We focus on distributions satisfying the minimal assumption that they have a…

Statistics Theory · Mathematics 2020-11-13 Christos Tzamos , Emmanouil-Vasileios Vlatakis-Gkaragkounis , Ilias Zadik

We show that under minimal assumptions on a class of functions $\mathcal{H}$ defined on a probability space $(\mathcal{X},\mu)$, there is a threshold $\Delta_0$ satisfying the following: for every $\Delta\geq\Delta_0$, with probability at…

Probability · Mathematics 2025-08-05 Daniel Bartl , Shahar Mendelson

This is an elementary introduction to infinite-dimensional probability. In the lectures, we compute the exact mean values of some functionals on C[0,1] and L[0,1] by considering these functionals as infinite-dimensional random variables.…

Probability · Mathematics 2017-05-11 Cheng-shi Liu

We estimate the size of a most loaded bin in the setting when the balls are placed into the bins using a random linear function in a finite field. The balls are chosen from a transformed interval. We show that in this setting the expected…

Data Structures and Algorithms · Computer Science 2015-01-05 Martin Babka

We consider the variable-to-fixed length lossy source coding (VFSC) problem. The optimal compression rate of the average length of variable-to-fixed source coding, allowing a non-vanishing probability of excess-distortion $\varepsilon$, is…

Information Theory · Computer Science 2018-03-20 Lan V. Truong , Vincent Y. F. Tan

We study the exact distributions of runs of a fixed length in variation which considers binary trials for which the probability of ones is geometrically varying. The random variable $E_{n,k}$ denote the number of success runs of a fixed…

Probability · Mathematics 2022-10-21 Jungtaek Oh , Dae-Gyu Jang

The normalized maximum likelihood code length has been widely used in model selection, and its favorable properties, such as its consistency and the upper bound of its statistical risk, have been demonstrated. This paper proposes a novel…

Statistics Theory · Mathematics 2018-01-12 Atsushi Suzuki , Kenji Yamanishi

We consider the maximum coding rate achievable by uniformly-random codes for the deletion channel. We prove an upper bound that's within 0.1 of the best known lower bounds for all values of the deletion probability $d,$ and much closer for…

Information Theory · Computer Science 2022-10-17 Berivan Isik , Francisco Pernice , Tsachy Weissman

We consider constructing capacity-achieving linear codes with minimum message size for private information retrieval (PIR) from $N$ non-colluding databases, where each message is coded using maximum distance separable (MDS) codes, such that…

Information Theory · Computer Science 2020-01-24 Ruida Zhou , Chao Tian , Hua Sun , Tie Liu

Given sufficiently many components, it is often cited that finite mixture models can approximate any other probability density function (pdf) to an arbitrary degree of accuracy. Unfortunately, the nature of this approximation result is…

Statistics Theory · Mathematics 2020-08-24 T Tin Nguyen , Hien D Nguyen , Faicel Chamroukhi , Geoffrey J McLachlan

A major bottleneck of standard auto-regressive large language models is that their inference process is inherently sequential, resulting in very long and costly inference times. To circumvent this, practitioners proposed a class of language…

Machine Learning · Computer Science 2025-11-11 Sitan Chen , Kevin Cong , Jerry Li

Universal source coding at short blocklengths is considered for an exponential family of distributions. The \emph{Type Size} code has previously been shown to be optimal up to the third-order rate for universal compression of all memoryless…

Information Theory · Computer Science 2016-12-21 Nematollah Iri , Oliver Kosut

In this paper we will estimate the main parameters of some evaluation codes which are known as projective parameterized codes. We will find the length of these codes and we will give a formula for the dimension in terms of the Hilbert…

Information Theory · Computer Science 2011-12-16 Manuel Gonzalez Sarabia , Carlos Renteria Marquez , Eliseo Sarmiento Rosales

We consider transmission of discrete memoryless sources (DMSes) across discrete memoryless channels (DMCs) using variable-length lossy source-channel codes with feedback. The reliability function (optimum error exponent) is shown to be…

Information Theory · Computer Science 2019-04-09 Lan V. Truong , Vincent Y. F. Tan

This paper provides a unifying view of a wide range of problems of interest in machine learning by framing them as the minimization of functionals defined on the space of probability measures. In particular, we show that generative…

Machine Learning · Computer Science 2019-05-21 Casey Chu , Jose Blanchet , Peter Glynn

Estimations of physical parameters using data usually involve non-uniform experimental efficiencies. In this article, a method of maximum likelihood fit is introduced using the efficiency as a weight, while the probability distribution…

Data Analysis, Statistics and Probability · Physics 2023-08-31 Chenxu Yu , Yanxi Zhang