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Let $\R(\cdot)$ stand for the bounded-error randomized query complexity. We show that for any relation $f \subseteq \{0,1\}^n \times \mathcal{S}$ and partial Boolean function $g \subseteq \{0,1\}^n \times \{0,1\}$, $\R_{1/3}(f \circ g^n) =…

Computational Complexity · Computer Science 2018-01-11 Swagato Sanyal

We study the problem of estimating the covariance parameters of a one-dimensional Gaussian process with exponential covariance function under fixed-domain asymptotics. We show that the weighted pairwise maximum likelihood estimator of the…

Statistics Theory · Mathematics 2019-07-15 François Bachoc , Moreno Bevilacqua , Daira Velandia

We consider two-dimensional L\'evy processes reflected to stay in the positive quadrant. Our focus is on the non-standard regime when the mean of the free process is negative but the reflection vectors point away from the origin, so that…

Probability · Mathematics 2024-03-25 Vladimir Fomichov , Sandro Franceschi , Jevgenijs Ivanovs

We generalize the result of Brandenbursky and Marcinkowski for the bounded cohomology of transformation groups to infinite volume case. To state the result, we introduce the notion of norm controlled cohomology as a generalization of…

Geometric Topology · Mathematics 2023-02-16 Mitsuaki Kimura

The proposal and study of dependent prior processes has been a major research focus in the recent Bayesian nonparametric literature. In this paper, we introduce a flexible class of dependent nonparametric priors, investigate their…

Statistics Theory · Mathematics 2014-07-03 Antonio Lijoi , Bernardo Nipoti , Igor Prünster

We investigate the dynamics of forward or backward self-similar systems (iterated function systems) and the topological structure of their invariant sets. We define a new cohomology theory (interaction cohomology) for forward or backward…

Dynamical Systems · Mathematics 2009-08-06 Hiroki Sumi

Infinite sets of inequalities which generalize all the known inequalities that can be used in the majorization step of the Approximating Hamiltonian method are derived. They provide upper bounds on the difference between the quadratic…

Mathematical Physics · Physics 2011-06-20 J. G. Brankov , N. S. Tonchev

We consider empirical processes generated by strictly stationary sequences of associated random variables. S. Louhichi established an invariance principle for such processes, assuming that the covariance function decays rapidly enough. We…

Probability · Mathematics 2015-09-28 Vadim Demichev

Even though strongly correlated systems are abundant, only a few exceptional cases admit analytical solutions. In this paper we present a large class of solvable systems with strong correlations.. We consider a set of $N$ independent and…

Statistical Mechanics · Physics 2024-01-04 Marco Biroli , Hernán Larralde , Satya N. Majumdar , Grégory Schehr

We give the proof of a tight lower bound on the probability that a binomial random variable exceeds its expected value. The inequality plays an important role in a variety of contexts, including the analysis of relative deviation bounds in…

Machine Learning · Computer Science 2013-11-12 Spencer Greenberg , Mehryar Mohri

The modeling of natural phenomena via a Markov process --- a process for which the future is independent of the past, given the present--- is ubiquitous in many fields of science. Within this context, it is of foremost importance to develop…

Quantum Physics · Physics 2020-03-24 Matheus Capela , Lucas C. Céleri , Kavan Modi , Rafael Chaves

A powerful statistical interpolating concept, which we call \emph{fully lifted} (fl), is introduced and presented while establishing a connection between bilinearly indexed random processes and their corresponding fully decoupled (linearly…

Probability · Mathematics 2023-12-01 Mihailo Stojnic

We study the Poisson (co)homology of the algebra of truncated polynomials in two variables viewed as the semi-classical limit of a quantum complete intersection studied by Bergh and Erdmann. We show in particular that the Poisson cohomology…

K-Theory and Homology · Mathematics 2008-06-02 Stephane Launois , Lionel Richard

Max-stable processes are widely used to model spatial extremes. These processes exhibit asymptotic dependence meaning that the large values of the process can occur simultaneously over space. Recently, inverted max-stable processes have…

Probability · Mathematics 2015-01-20 Ioannis Papastathopoulos , Jonathan A. Tawn

We present the first experimental confirmation of the quantum-mechanical prediction of stronger-than-binary correlations. These are correlations that cannot be explained under the assumption that the occurrence of a particular outcome of an…

We find a sharp combinatorial bound for the metric entropy of sets in R^n and general classes of functions. This solves two basic combinatorial conjectures on the empirical processes. 1. A class of functions satisfies the uniform Central…

Functional Analysis · Mathematics 2016-12-23 Mark Rudelson , Roman Vershynin

Commonalities and differences in correlation analysis in terms of phase space, conditioning and uncorrelatedness are discussed. The Poisson process is not generally appropriate as reference distribution for normalisation and cumulants, so…

High Energy Physics - Experiment · Physics 2007-05-23 H. C. Eggers

We introduce the notion of pullback along a measurable cocycle and we use it to extend the Borel invariant studied by Bucher, Burger and Iozzi to the world of measurable cocycles. The Borel invariant is constant along cohomology classes and…

Geometric Topology · Mathematics 2022-01-03 Alessio Savini

We study a class of Gaussian processes for which the posterior mean, for a particular choice of data, replicates a truncated Taylor expansion of any order. The data consist of derivative evaluations at the expansion point and the prior…

Machine Learning · Computer Science 2023-08-29 Toni Karvonen , Jon Cockayne , Filip Tronarp , Simo Särkkä

Dependent nonparametric processes extend distributions over measures, such as the Dirichlet process and the beta process, to give distributions over collections of measures, typically indexed by values in some covariate space. Such models…

Machine Learning · Statistics 2012-11-21 Nicholas J. Foti , Sinead Williamson