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The exact expression is derived for the expected value, $< {p_i}> $, for the parameter for any bin $i$ of a histogram following a multinomial distribution derived by sorting $N$ observations into bins of $B$ classes, if $n_i$ of the…

Statistics Theory · Mathematics 2013-03-18 Jonathan M. Friedman

We study the problem of estimating the average of a Lipschitz continuous function $f$ defined over a metric space, by querying $f$ at only a single point. More specifically, we explore the role of randomness in drawing this sample. Our goal…

Data Structures and Algorithms · Computer Science 2011-01-21 Abhimanyu Das , David Kempe

Two distinct distribution functions $P_{sp}(m)$ and $P_{ns}(m)$ of the scaled largest cluster sizes $m$ are obtained at the percolation threshold by numerical simulations, depending on the condition whether the lattice is actually spanned…

Disordered Systems and Neural Networks · Physics 2009-11-07 Parongama Sen

We provide an efficient unified plug-in approach for estimating symmetric properties of distributions given $n$ independent samples. Our estimator is based on profile-maximum-likelihood (PML) and is sample optimal for estimating various…

Machine Learning · Statistics 2022-10-14 Moses Charikar , Zhihao Jiang , Kirankumar Shiragur , Aaron Sidford

We consider maximum likelihood estimation of finite mixture of uniform distributions. We prove that maximum likelihood estimator is strongly consistent, if the scale parameters of the component uniform distributions are restricted from…

Statistics Theory · Mathematics 2007-06-13 Kentaro Tanaka , Akimichi Takemura

We obtain approximation results for general positive linear operators satisfying mild conditions, when acting on discontinuous functions and absolutely continuous functions having discontinuous derivatives. The upper bounds, given in terms…

Probability · Mathematics 2024-10-29 José A. Adell , P. Garrancho , F. J. Martínez-Sánchez

Distribution matching is the process of invertibly mapping a uniformly distributed input sequence onto sequences that approximate the output of a desired discrete memoryless source. The special case of a binary output alphabet and…

Information Theory · Computer Science 2017-12-19 Patrick Schulte , Bernhard C. Geiger

This paper investigates the stability of the least squares approximation $P_m^n$ within the univariate polynomial space of degree $m$, denoted by ${\mathbb P}_m$. The approximation $P_m^n$ entails identifying a polynomial in ${\mathbb P}_m$…

Numerical Analysis · Mathematics 2026-02-17 Zhiqiang Xu , Xinyue Zhang

We consider the problem of computing a function of $n$ variables using noisy queries, where each query is incorrect with some fixed and known probability $p \in (0,1/2)$. Specifically, we consider the computation of the $\mathsf{OR}$…

Data Structures and Algorithms · Computer Science 2023-09-11 Banghua Zhu , Ziao Wang , Nadim Ghaddar , Jiantao Jiao , Lele Wang

Variable-length compression without prefix-free constraints and with side-information available at both encoder and decoder is considered. Instead of requiring the code to be error-free, we allow for it to have a non-vanishing error…

Information Theory · Computer Science 2020-08-24 Yuta Sakai , Vincent Y. F. Tan

Fitting probabilistic models to data is often difficult, due to the general intractability of the partition function. We propose a new parameter fitting method, Minimum Probability Flow (MPF), which is applicable to any parametric model. We…

Machine Learning · Computer Science 2020-07-21 Jascha Sohl-Dickstein , Peter Battaglino , Michael R. DeWeese

Information functionals allow to quantify the degree of randomness of a given probability distribution, either absolutely (through min/max entropy principles) or relative to a prescribed reference one. Our primary aim is to analyze the…

Quantum Physics · Physics 2007-11-22 Piotr Garbaczewski

We consider the problem of estimating a mixture of power series distributions with infinite support, to which belong very well-known models such as Poisson, Geometric, Logarithmic or Negative Binomial probability mass functions. We consider…

Statistics Theory · Mathematics 2025-08-04 Fadoua Balabdaoui , Harald Besdziek , Yong Wang

Given Mikhlin-H\"ormander multipliers $m_i$, $i=1,..., N$, with uniform estimates we prove an optimal $\sqrt{\log(N+1)}$ bound in $L^p$ for the maximal function $\sup_i|\cF^{-1}[m_i\hat f]|$ and related bounds for maximal functions…

Classical Analysis and ODEs · Mathematics 2010-03-15 Loukas Grafakos , Petr Honzik , Andreas Seeger

If p is the probability of a letter of a memoryless source, the length l of the corresponding binary Huffman codeword can be very different from the value -log p. We show that, nevertheless, for a typical letter, l is approximately equal to…

adap-org · Physics 2008-02-03 R. Schack

Probability functions appear in constraints of many optimization problems in practice and have become quite popular. Understanding their first-order properties has proven useful, not only theoretically but also in implementable algorithms,…

Optimization and Control · Mathematics 2023-04-21 Wim van Ackooij , Pedro Pérez-Aros , Claudia Soto

Given a sufficient statistic for a parametric family of distributions, one can estimate the parameter without access to the data. However, the memory or code size for storing the sufficient statistic may nonetheless still be prohibitive.…

Information Theory · Computer Science 2017-11-17 Masahito Hayashi , Vincent Y. F. Tan

We study the expected value of the length $L_n$ of the minimum spanning tree of the complete graph $K_n$ when each edge $e$ is given an independent uniform $[0,1]$ edge weight. We sharpen the result of Frieze \cite{F1} that…

Combinatorics · Mathematics 2019-02-20 Colin Cooper , Alan Frieze , Nate Ince , Svante Janson , Joel Spencer

In this article, we proposed a new probability distribution named as power Maxwell distribution (PMaD). It is another extension of Maxwell distribution (MaD) which would lead more flexibility to analyze the data with non-monotone failure…

Applications · Statistics 2018-07-04 Abhimanyu Singh Yadav , Hassan S. Bakouch , Sanjay Kumar Singh , Umesh Singh

The theorem states that: Every Boolean function can be $\epsilon -approximated$ by a Disjunctive Normal Form (DNF) of size $O_{\epsilon}(2^{n}/\log{n})$. This paper will demonstrate this theorem in detail by showing how this theorem is…

Computational Complexity · Computer Science 2020-05-13 Yunhao Yang , Andrew Tan