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In quantum theory, physically measurable quantities of a microscopic system are represented by self-adjoint operators. However, not all of the self-adjoint operators correspond to measurable quantities. The superselection rule is a…

Quantum Physics · Physics 2011-12-30 Shogo Tanimura

In this paper, we consider a multi-drawing urn model with random addition. At each discrete time step, we draw a sample of m balls. According to the composition of the drawn colors, we return the balls together with a random number of balls…

Probability · Mathematics 2018-02-14 Rafik Aguech , Nabil Lasmar , Olfa Selmi

Based on previous work of Paul Ressel and myself, I show that the space of all "continuous" exchangeable probability measures on a certain set of order processes is a Bauer simplex.

Probability · Mathematics 2007-05-23 Ulrich Hirth

The Shapley value is commonly illustrated by roll call votes in which players support or reject a proposal in sequence. If all sequences are equiprobable, a voter's Shapley value can be interpreted as the probability of being pivotal, i.e.,…

Computer Science and Game Theory · Computer Science 2018-10-04 Sascha Kurz , Stefan Napel

Parallel tempering (PT) methods are a popular class of Markov chain Monte Carlo schemes used to sample complex high-dimensional probability distributions. They rely on a collection of $N$ interacting auxiliary chains targeting tempered…

Computation · Statistics 2021-07-28 Saifuddin Syed , Alexandre Bouchard-Côté , George Deligiannidis , Arnaud Doucet

Maximum diversity problems arise in many practical settings from facility location to social networks, and constitute an important class of NP-hard problems in combinatorial optimization. There has been a growing interest in these problems…

Optimization and Control · Mathematics 2024-01-25 Francisco Parreño , Ramón Álvarez-Valdés , Rafael Martí

Let $Y$ be a nonnegative random variable with mean $\mu$ and finite positive variance $\sigma^2$, and let $Y^s$, defined on the same space as $Y$, have the $Y$ size biased distribution, that is, the distribution characterized by…

Probability · Mathematics 2011-06-20 Subhankar Ghosh , Larry Goldstein

Kernel mean embeddings are a popular tool that consists in representing probability measures by their infinite-dimensional mean embeddings in a reproducing kernel Hilbert space. When the kernel is characteristic, mean embeddings can be used…

Machine Learning · Computer Science 2021-06-29 Boris Muzellec , Francis Bach , Alessandro Rudi

Generalized probability distributions for Maxwell-Boltzmann, Bose-Einstein and Fermi-Dirac statistics, with unequal source probabilities $q_i$ for each level $i$, are obtained by combinatorial reasoning. For equiprobable degenerate…

Statistical Mechanics · Physics 2008-08-18 Robert K. Niven , Marian Grendar

Exchangeability -- in which the distribution of an infinite sequence is invariant to reorderings of its elements -- implies the existence of a simple conditional independence structure that may be leveraged in the design of statistical…

Statistics Theory · Mathematics 2022-07-25 Trevor Campbell , Saifuddin Syed , Chiao-Yu Yang , Michael I. Jordan , Tamara Broderick

In this work we analyze the concept of swap-invariance, which is a weaker variant of exchangeability. A random vector $\xi$ in $\mathbb{R}^n$ is called swap-invariant if $\,{\mathbf E}\,\big| \!\sum_j u_j \xi_j \big|\,$ is invariant under…

Probability · Mathematics 2016-07-06 Felix Nagel

Our object of study is the general class of stick-breaking processes with exchangeable length variables. These generalize well-known Bayesian non-parametric priors in an unexplored direction. We give conditions to assure the respective…

Statistics Theory · Mathematics 2021-07-20 María F. Gil-Leyva , Ramsés H. Mena

The main result in this paper is motivated by the M\'ezard-Parisi ansatz which predicts a very special structure for the distribution of spins in diluted mean field spin glass models, such as the random K-sat model. Using the fact that one…

Probability · Mathematics 2015-04-14 Dmitry Panchenko

Probabilistic mixture models are recognized as effective tools for unsupervised outlier detection owing to their interpretability and global characteristics. Among these, Dirichlet process mixture models stand out as a strong alternative to…

Machine Learning · Computer Science 2024-07-26 Dongwook Kim , Juyeon Park , Hee Cheol Chung , Seonghyun Jeong

We introduce a new concept of dissipative measure-valued martingale solutions to the stochastic compressible Euler equations. These solutions are weak in the probabilistic sense i.e., the probability space and the driving Wiener process are…

Analysis of PDEs · Mathematics 2020-12-15 Martina Hofmanova , Ujjwal Koley , Utsab Sarkar

We consider Wald type statistics designed for joint predictability and structural break testing based on the instrumentation method of Phillips and Magdalinos (2009). We show that under the assumption of nonstationary predictors: (i) the…

Econometrics · Economics 2023-07-31 Christis Katsouris

Kernel mean embeddings have recently attracted the attention of the machine learning community. They map measures $\mu$ from some set $M$ to functions in a reproducing kernel Hilbert space (RKHS) with kernel $k$. The RKHS distance of two…

Machine Learning · Statistics 2019-12-18 Carl-Johann Simon-Gabriel , Bernhard Schölkopf

We consider a system of urns of Polya-type, with balls of two colors; the reinforcement of each urn depends both on the content of the same urn and on the average content of all urns. We show that the urns synchronize almost surely, in the…

Probability · Mathematics 2016-03-08 Paolo Dai Pra , Pierre-Yves Louis , Ida G. Minelli

The experimentally measured multiplicity distributions exhibit, after closer inspection, peculiarly enhanced void probability and oscillatory behavior of the modified combinants. We show that both these features can be used as additional…

High Energy Physics - Phenomenology · Physics 2019-09-05 M. Rybczynski , Z. Wlodarczyk , G. Wilk

In this paper, we study discrete-time absorbing Markov Decision Processes (MDP) with measurable state space and Borel action space with a given initial distribution. For such models, solutions to the characteristic equation that are not…

Optimization and Control · Mathematics 2025-10-10 François Dufour , Tomás Prieto-Rumeau