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The mutual information (MI) between two random variables is an important correlation measure in data analysis. The Shannon entropy of a joint probability distribution is the variable part under fixed marginals. We aim to minimize and…

Optimization and Control · Mathematics 2025-09-08 Paula Franke , Kay Hamacher , Paul Manns

The optimization problem that arises out of the least median of squared residuals method in linear regression is analyzed. To simplify the analysis, the problem is replaced by an equivalent one of minimizing the median of absolute…

Optimization and Control · Mathematics 2015-10-15 Nikolai Krivulin

Let p_n denote the persistence probability that the first n iterated partial sums of integrable, zero-mean, i.i.d. random variables X_k, are negative. We show that p_n is bounded above up to universal constant by the square root of the…

Probability · Mathematics 2011-02-01 Amir Dembo , Fuchang Gao

Gaussian process regression is a powerful Bayesian nonlinear regression method. Recent research has enabled the capture of many types of observations using non-Gaussian likelihoods. To deal with various tasks in spatial modeling, we benefit…

Machine Learning · Statistics 2025-08-26 Yuta Shikuri

We consider the variable selection problem in linear regression. Suppose that we have a set of random variables $X_1,...,X_m,Y,\epsilon$ such that $Y=\sum_{k\in \pi}\alpha_kX_k+\epsilon$ with $\pi\subseteq \{1,...,m\}$ and $\alpha_k\in…

Statistics Theory · Mathematics 2010-12-21 Joe Suzuki

We consider the Minimum Description Length principle for online sequence prediction. If the underlying model class is discrete, then the total expected square loss is a particularly interesting performance measure: (a) this quantity is…

Machine Learning · Computer Science 2007-07-16 Jan Poland , Marcus Hutter

In this paper, we consider the nonasymptotic sequential estimation of means of random variables bounded in between zero and one. We have rigorously demonstrated that, in order to guarantee prescribed relative precision and confidence level,…

Statistics Theory · Mathematics 2013-11-05 Xinjia Chen

Quantile regression is a powerful tool for inferring how covariates affect specific percentiles of the response distribution. Existing methods either estimate conditional quantiles separately for each quantile of interest or estimate the…

Methodology · Statistics 2024-11-19 Joseph Feldman , Daniel Kowal

We propose a class of models with gauge mediation of supersymmetry breaking, inspired by simple brane constructions, where R-symmetry is very weakly broken. The gauge sector has an extended N=2 supersymmetry and the two electroweak Higgses…

High Energy Physics - Phenomenology · Physics 2008-11-26 I. Antoniadis , K. Benakli , A. Delgado , M. Quiros

Let $X_1,X_2,...,X_n$ be a sequence of independent or locally dependent random variables taking values in $\mathbb{Z}_+$. In this paper, we derive sharp bounds, via a new probabilistic method, for the total variation distance between the…

Statistics Theory · Mathematics 2010-10-11 Michael V. Boutsikas , Eutichia Vaggelatou

We show that simultaneous gauge and supersymmetry breaking can be induced by radiative corrections, a la Coleman-Weinberg. When a certain correlation among the superpotential parameters is present, a local supersymmetry-breaking minimum is…

High Energy Physics - Phenomenology · Physics 2017-08-23 Borut Bajc , Stéphane Lavignac , Timon Mede

The paper studies the problem of distributed average consensus in sensor networks with quantized data and random link failures. To achieve consensus, dither (small noise) is added to the sensor states before quantization. When the quantizer…

Multiagent Systems · Computer Science 2009-09-28 Soummya Kar , Jose M. F. Moura

Let $X=(X_1,\ldots,X_n)$ be a vector of i.i.d. random variables where $X_i$'s take values over $\mathbb{N}$. The purpose of this paper is to study the number of weakly increasing subsequences of $X$ of a given length $k$, and the number of…

Probability · Mathematics 2018-05-15 Ümit Işlak , Alperen Y. Özdemir

The sampling, quantization, and estimation of a bounded dynamic-range bandlimited signal affected by additive independent Gaussian noise is studied in this work. For bandlimited signals, the distortion due to additive independent Gaussian…

Information Theory · Computer Science 2012-11-29 Animesh Kumar , Vinod M. Prabhakaran

This paper studies the behavior of singularly perturbed nonlinear differential equations with boundary-layer solutions that do not necessarily converge to an equilibrium. Using the average of the fast variable and assuming the boundary…

Systems and Control · Computer Science 2018-09-24 Mohammad Deghat , Saeed Ahmadizadeh , Dragan Nesic , Chris Manzie

The minimum mean-square error of the estimation of a signal where observed from the additive white Gaussian noise (WGN) channel's output, is analyzed. It is assumed that the channel input's signal is composed of a (normalized) sum of N…

Information Theory · Computer Science 2007-07-13 Jacob Binia

We show that the set of atoms of the limiting empirical marginal distribution in the random $2$-SAT model is $\mathbb Q \cap (0,1)$, for all clause-to-variable densities up to the satisfiability threshold. While for densities up to $1/2$,…

Probability · Mathematics 2024-10-24 Noela Müller , Ralph Neininger , Haodong Zhu

Let $K_n$ denote the number of types of a sample of size $n$ taken from an exchangeable coalescent process ($\Xi$-coalescent) with mutation. A distributional recursion for the sequence $(K_n)_{n\in{\mathbb N}}$ is derived. If the coalescent…

Probability · Mathematics 2008-08-14 Fabian Freund , Martin Möhle

For many important problems the quantity of interest is an unknown function of the parameters, which is a random vector with known statistics. Since the dependence of the output on this random vector is unknown, the challenge is to identify…

Machine Learning · Statistics 2021-04-28 Themistoklis P. Sapsis

We introduce a new methodology for analyzing serial data by quantile regression assuming that the underlying quantile function consists of constant segments. The procedure does not rely on any distributional assumption besides serial…

Methodology · Statistics 2020-09-09 Laura Jula Vanegas , Merle Behr , Axel Munk
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