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Functional panels are collections of functional time series, and arise often in the study of high frequency multivariate data. We develop a portmanteau style test to determine if the cross-sections of such a panel are independent and…

Methodology · Statistics 2016-07-12 Piotr Kokoszka , Matthew Reimherr , Nikolas Wölfing

In the paper I study properties of random polynomials with respect to a general system of functions. Some lower bounds for the mathematical expectation of the uniform and recently introduced integral-uniform norms of random polynomials are…

Probability · Mathematics 2007-05-23 Pavel Grigoriev

An optimal bound on the quantiles of a certain kind of distributions is given. Such a bound is used in applications to Berry--Esseen-type bounds for nonlinear statistics.

Probability · Mathematics 2013-01-03 Iosif Pinelis

We consider the statistical deconvolution problem where one observes $n$ replications from the model $Y=X+\epsilon$, where $X$ is the unobserved random signal of interest and $\epsilon$ is an independent random error with distribution…

Statistics Theory · Mathematics 2011-03-09 Karim Lounici , Richard Nickl

This paper considers a distributionally robust chance constraint model with a general ambiguity set. We show that a sample based approximation of this model converges under suitable sufficient conditions. We also show that upper and lower…

Optimization and Control · Mathematics 2025-01-17 Jiaqi Lei , Sanjay Mehrotra

The "theoretical limit of time-frequency resolution in Fourier analysis" is thought to originate in certain mathematical and/or physical limitations. This, however, is not true. The actual origin arises from the numerical (technical) method…

Physics and Society · Physics 2025-03-28 Fumihiko Ishiyama

We use the exact finite sample likelihood and statistical decision theory to answer questions of ``why?'' and ``what should you have done?'' using data from randomized experiments and a utility function that prioritizes safety over…

Econometrics · Economics 2024-07-26 Neil Christy , A. E. Kowalski

Estimates are constructed for the deviation of the concentration functions of sums of independent random variables with finite variances from the folded normal distribution function without any assumptions concerning the existence of the…

Probability · Mathematics 2016-08-11 V. Yu. Korolev , A. V. Dorofeeva

In this paper we study the behaviour at infinity of the Fourier transform of Radon measures supported by the images of fractal sets under an algorithmically random Brownian motion. We show that, under some computability conditions on these…

Computational Complexity · Computer Science 2015-07-01 Willem Louw Fouché , Safari Mukeru , George Davie

We present an algorithm based on posterior sampling (aka Thompson sampling) that achieves near-optimal worst-case regret bounds when the underlying Markov Decision Process (MDP) is communicating with a finite, though unknown, diameter. Our…

Machine Learning · Computer Science 2020-04-01 Shipra Agrawal , Randy Jia

The article addresses a long-standing open problem on the justification of using variational Bayes methods for parameter estimation. We provide general conditions for obtaining optimal risk bounds for point estimates acquired from…

Statistics Theory · Mathematics 2017-12-27 Debdeep Pati , Anirban Bhattacharya , Yun Yang

It is shown that at least 50% of the probability mass of a sum of independent Rademacher random variables is within one standard deviation from its mean. This lower bound is sharp, it is much better than for instance the bound that can be…

Probability · Mathematics 2011-12-22 Martien C. A. van Zuijlen

Consider a rowwise independent triangular array of gamma random variables with varying parameters. Under several different conditions on the shape parameter, we show that the sequence of row-maximums converges weakly after linear or power…

Probability · Mathematics 2009-03-06 Arup Bose , Amites Dasgupta , Krishanu Maulik

Using a capacity approach, and the theory of measure's perturbation of Dirichlet forms, we give the probabilistic representation of the General Robin boundary value problems on an arbitrary domain $\Omega$, involving smooth measures, which…

Probability · Mathematics 2013-03-26 Khalid Akhlil

Existing convolutional neural networks widely adopt spatial down-/up-sampling for multi-scale modeling. However, spatial up-sampling operators (\emph{e.g.}, interpolation, transposed convolution, and un-pooling) heavily depend on local…

Computer Vision and Pattern Recognition · Computer Science 2022-10-12 Man Zhou , Hu Yu , Jie Huang , Feng Zhao , Jinwei Gu , Chen Change Loy , Deyu Meng , Chongyi Li

Coherent diffractive imaging (CDI) provides new opportunities for high resolution X-ray imaging with simultaneous amplitude and phase contrast. Extensions to CDI broaden the scope of the technique for use in a wide variety of experimental…

Optics · Physics 2016-01-20 Matthew H. Seaberg , Alexandre d'Aspremont , Joshua J. Turner

In this paper, we provide extended convolution bounds for the Fr\'{e}chet problem and discuss related implications in quantitative risk management. First, we establish a new form of inequality for the Range-Value-at-Risk (RVaR). Based on…

Risk Management · Quantitative Finance 2025-12-01 Peng Liu , Yang Liu , Houhan Teng

Condorcet domains are sets of linear orders with the property that, whenever voters' preferences are restricted to the domain, the pairwise majority relation (for an odd number of voters) is transitive and hence a linear order. Determining…

Discrete Mathematics · Computer Science 2026-01-13 Alexander Karpov , Klas Markstrom , Soren Riis , Bei Zhou

We leverage proof techniques Fourier analysis and an existing result in coding theory to derive new bounds for the problem of non-interactive simulation of binary random variables. Previous bounds in the literature were derived by applying…

Information Theory · Computer Science 2021-01-26 Lei Yu , Vincent Y. F. Tan

We present some extensions of Bernstein's concentration inequality for random matrices. This inequality has become a useful and powerful tool for many problems in statistics, signal processing and theoretical computer science. The main…

Probability · Mathematics 2017-04-18 Stanislav Minsker