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Many applications in the field of statistics require Markov chain Monte Carlo methods. Determining appropriate starting values and run lengths can be both analytically and empirically challenging. A desire to overcome these problems has led…

Computation · Statistics 2012-03-09 James M. Flegal , Radu Herbei

Given a stream of Bernoulli random variables, consider the problem of estimating the mean of the random variable within a specified relative error with a specified probability of failure. Until now, the Gamma Bernoulli Approximation Scheme…

Machine Learning · Computer Science 2022-10-25 Mark Huber

Here several perfect simulation algorithms are brought under a single framework, and shown to derive from the same probabilistic result, called here the Fundamental Theorem of Perfect Simulation (FTPS). An exact simulation algorithm has…

Probability · Mathematics 2017-04-13 Mark Huber

We study properties of confidence intervals (CIs) for the difference of two Bernoulli distributions' success parameters, $p_x - p_y$, in the case where the goal is to obtain a CI of a given half-width while minimizing sampling costs when…

Methodology · Statistics 2023-11-23 Ignacio Erazo , David Goldsman , Yajun Mei

We present a novel way of generating Lyapunov functions for proving linear convergence rates of first-order optimization methods. Our approach provably obtains the fastest linear convergence rate that can be verified by a quadratic Lyapunov…

Optimization and Control · Mathematics 2018-06-13 Adrien Taylor , Bryan Van Scoy , Laurent Lessard

We consider the problem of estimating the parameters of a multivariate Bernoulli process with auto-regressive feedback in the high-dimensional setting where the number of samples available is much less than the number of parameters. This…

Statistics Theory · Mathematics 2019-03-25 Parthe Pandit , Mojtaba Sahraee-Ardakan , Arash A. Amini , Sundeep Rangan , Alyson K. Fletcher

The process generates substantial amounts of data with highly complex structures, leading to the development of numerous nonlinear statistical methods. However, most of these methods rely on computations involving large-scale dense kernel…

Machine Learning · Statistics 2025-03-18 Ke Chen , Dandan Jiang

We consider a classical scheduling problem on $m$ identical machines. For an arbitrary constant $q>1$, the aim is to assign jobs to machines such that $\sum_{i=1}^m C_i^q$ is minimized, where $C_i$ is the total processing time of jobs…

Computational Complexity · Computer Science 2021-07-14 Lin Chen , Liangde Tao , José Verschae

We propose an optimal sequential methodology for obtaining confidence intervals for a binomial proportion $\theta$. Assuming that an i.i.d. random sequence of Benoulli($\theta$) trials is observed sequentially, we are interested in…

Methodology · Statistics 2017-11-21 Tony Yaacoub , George V. Moustakides , Yajun Mei

We consider search by mobile agents for a hidden, idle target, placed on the infinite line. Feasible solutions are agent trajectories in which all agents reach the target sooner or later. A special feature of our problem is that the agents…

Data Structures and Algorithms · Computer Science 2023-03-29 Konstantinos Georgiou , Nikos Giachoudis , Evangelos Kranakis

We study in-network computation on general network topologies. Specifically, we are given the description of a function, and a network with distinct nodes at which the operands of the function are made available, and a designated sink where…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-06-22 Iqra Altaf Gillani , Pooja Vyavahare , Amitabha Bagchi

In this article, we show that a linear combination $X$ of $n$ independent, unbiased Bernoulli random variables $\{X_k\}$ can match the first $2n$ moments of a random variable $Y$ which is uniform on an interval. More generally, for each $p…

Probability · Mathematics 2019-09-16 Greg Kuperberg

In this paper we prove a L\'evy-Ottaviani type of property for the Bernoulli process defined on an interval. Namely, we show that under certain conditions on functions $(a_i)_{i=1}^{n}$ and for independent Bernoulli random variables…

Probability · Mathematics 2019-11-14 Witold Bednorz , Rafał Martynek

Let $p$ be an unknown and arbitrary probability distribution over $[0,1)$. We consider the problem of {\em density estimation}, in which a learning algorithm is given i.i.d. draws from $p$ and must (with high probability) output a…

Machine Learning · Computer Science 2014-11-04 Siu-On Chan , Ilias Diakonikolas , Rocco A. Servedio , Xiaorui Sun

Let $\BS_1,...,\BS_n$ be independent identically distributed random variables each having the standardized Bernoulli distribution with parameter $p\in(0,1)$. Let $m_*(p):=(1+p+2p^2)/(2\sqrt{p-p^2}+4p^2)$ if $0<p\le 1/2$ and $m_*(p):=1$ if…

Probability · Mathematics 2007-12-23 Iosif Pinelis

Discovery problems often require deciding whether additional sampling is needed to detect all categories whose prevalence exceeds a prespecified threshold. We study this question under a Bernoulli product (incidence) model, where categories…

Methodology · Statistics 2026-01-29 Alessandro Colombi , Mario Beraha , Amichai Painsky , Stefano Favaro

Consider a binary tree, to the vertices of which are assigned independent Bernoulli random variables with mean $p\leq1/2$. How many of these Bernoullis one must look at in order to find a path of length $n$ from the root which maximizes, up…

Probability · Mathematics 2009-09-02 Robin Pemantle

We present a randomized algorithm for estimating the $p$th moment $F_p$ of the frequency vector of a data stream in the general update (turnstile) model to within a multiplicative factor of $1 \pm \epsilon$, for $p > 2$, with high constant…

Data Structures and Algorithms · Computer Science 2015-06-05 Sumit Ganguly

Let us assume that $f$ is a continuous function defined on the unit ball of $\mathbb R^d$, of the form $f(x) = g (A x)$, where $A$ is a $k \times d$ matrix and $g$ is a function of $k$ variables for $k \ll d$. We are given a budget $m \in…

Numerical Analysis · Mathematics 2012-01-18 Massimo Fornasier , Karin Schnass , Jan Vybiral

In this paper, we study the rate distortion function of the i.i.d sequence of multiplications of a Bernoulli $p$ random variable and a gaussian random variable $\sim N(0,1)$. We use a new technique in the derivation of the lower bound in…

Information Theory · Computer Science 2016-11-15 Cheng Chang