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In this article we prove that for any orthonormal system $(\vphi_j)_{j=1}^n \subset L_2$ that is bounded in $L_{\infty}$, and any $1 < k <n$, there exists a subset $I$ of cardinality greater than $n-k$ such that on $\spa\{\vphi_i\}_{i \in…

Functional Analysis · Mathematics 2008-01-24 Olivier Guedon , Shahar Mendelson , Alain Pajor , Nicole Tomczak-Jaegermann

We consider the problem of rationalizing choice data by a preference satisfying an arbitrary collection of invariance axioms. Examples of such axioms include quasilinearity, homotheticity, independence-type axioms for mixture spaces,…

Theoretical Economics · Economics 2024-08-09 Peter Caradonna , Christopher P. Chambers

The dynamics of quantum information in many-body systems with large onsite Hilbert space dimension admits an enlightening description in terms of effective statistical mechanics models. Motivated by this fact, we reveal a connection between…

Quantum Physics · Physics 2025-06-30 Andrew A. Allocca , Conner LeMaire , Thomas Iadecola , Justin H. Wilson

We study statistics on ordered set partitions whose generating functions are related to $p,q$-Stirling numbers of the second kind. The main purpose of this paper is to provide bijective proofs of all the conjectures of \stein…

Combinatorics · Mathematics 2007-12-12 Anisse Kasraoui , Jiang Zeng

We describe a measurement device principle based on discrete iterations of Bayesian updating of system state probability distributions. Although purely classical by nature, these measurements are accompanied with a progressive collapse of…

Mathematical Physics · Physics 2015-06-11 Michel Bauer , Denis Bernard , Tristan Benoist

We further study the asymptotics of quantization errors for two classes of in-homogeneous self-similar measures $\mu$. We give a new sufficient condition for the upper quantization coefficient for $\mu$ to be finite. This, together with our…

Metric Geometry · Mathematics 2016-09-01 Sanguo Zhu

A Peskun ordering between two samplers, implying a dominance of one over the other, is known among the Markov chain Monte Carlo community for being a remarkably strong result. It is however also known for being a result that is notably…

Computation · Statistics 2024-05-20 Philippe Gagnon , Florian Maire

We study the problem of assigning indivisible objects to agents where each is to receive at most one. To ensure fairness in the absence of monetary compensation, we consider random assignments. Random Priority, also known as Random Serial…

Theoretical Economics · Economics 2025-06-24 Christian Basteck

Stein's method allows to prove distributional convergence of a sequence of random variables and to quantify it with respect to a given metric such as Kolmogorov's (a Berry-Ess\'een type theorem). Mod-* convergence quantifies the convergence…

Probability · Mathematics 2017-01-12 Yacine Barhoumi-Andréani

Due to the absence of an external, classical time variable, the probabilistic predictions of covariant quantum theory are ambiguous when multiple measurements are considered. Here, we introduce an information theoretic framework to the…

Quantum Physics · Physics 2011-11-09 S. Jay Olson , Jonathan P. Dowling

Stochastic dominance is a technique for evaluating the performance of online algorithms that provides an intuitive, yet powerful stochastic order between the compared algorithms. Accordingly this holds for bijective analysis, which can be…

Data Structures and Algorithms · Computer Science 2016-07-22 Spyros Angelopoulos , Marc P. Renault , Pascal Schweitzer

We describe a general strategy for sampling configurations from a given (Gibbs-Boltzmann or other) distribution. It is {\it not} based on the Metropolis concept of establishing a Markov process whose stationary state is the wanted…

Statistical Mechanics · Physics 2007-05-23 P. Grassberger , W. Nadler

We prove tail and moment inequalities for multiple stochastic integrals on the Poisson space and for Poisson $U$-statistics. We use them to demonstrate the Law of the Iterated Logarithm for these processes when the intensity of the Poisson…

Probability · Mathematics 2024-08-09 Radosław Adamczak , Dominik Kutek

The majorization relation has been shown to be useful in classifying which transformations of jointly held quantum states are possible using local operations and classical communication. In some cases, a direct transformation between two…

Quantum Physics · Physics 2013-05-29 Sumit Daftuar , Matthew Klimesh

It has been found that stochastic algorithms often find good solutions much more rapidly than inherently-batch approaches. Indeed, a very useful rule of thumb is that often, when solving a machine learning problem, an iterative technique…

Machine Learning · Computer Science 2013-08-19 Andrew Cotter

Let $P=(x_1,\ldots,x_n)$ be a population consisting of $n\ge 2$ real numbers whose sum is zero, and let $k <n$ be a positive integer. We sample $k$ elements from $P$ without replacement and denote by $X_P$ the sum of the elements in our…

Probability · Mathematics 2025-03-27 Jianhang Ai , Ondřej Kuželka , Christos Pelekis

We consider the Moran process with two populations competing under an iterated Prisoners' Dilemma in the presence of mutation, and concentrate on the case where there are multiple Evolutionarily Stable Strategies. We perform a complete…

Dynamical Systems · Mathematics 2015-12-23 Lee DeVille , Meghan Galiardi

In this thesis we study convolutions that arise from noncommutative probability theory. We prove several regularity results for free convolutions, and for measures in partially defined one-parameter free convolution semigroups. We discuss…

Operator Algebras · Mathematics 2007-05-23 Serban Teodor Belinschi

Majorization inequalities have a long history, going back to Maclaurin and Newton. They were recently studied for several families of symmetric functions, including by Cuttler--Greene--Skandera (2011), Sra (2016), Khare--Tao (2021),…

Combinatorics · Mathematics 2026-02-16 Hong Chen , Apoorva Khare , Siddhartha Sahi

Spaces with locally varying scale of measurement, like multidimensional structures with differently scaled dimensions, are pretty common in statistics and machine learning. Nevertheless, it is still understood as an open question how to…

Machine Learning · Statistics 2024-03-05 Christoph Jansen , Georg Schollmeyer , Hannah Blocher , Julian Rodemann , Thomas Augustin