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We consider a version of a famous open problem formulated by Kadison, asking whether bounded representations of operator algebras are automatically completely bounded. We investigate this question in the context of amenable operator…

Operator Algebras · Mathematics 2017-08-02 Raphaël Clouâtre , Laurent W. Marcoux

The ability of likelihood-based probabilistic models to generalize to unseen data is central to many machine learning applications such as lossless compression. In this work, we study the generalization of a popular class of probabilistic…

Machine Learning · Statistics 2022-10-18 Mingtian Zhang , Peter Hayes , David Barber

Sorting is a common and ubiquitous activity for computers. It is not surprising that there exist a plethora of sorting algorithms. For all the sorting algorithms, it is an accepted performance limit that sorting algorithms are linearithmic…

Data Structures and Algorithms · Computer Science 2011-05-18 William F. Gilreath

We give an order-theoretic characterization of the essential image of the forgetful functor from the category of real/complex unital C*-algebras to the category of real/complex unital operator systems. It is based on the characterization of…

Operator Algebras · Mathematics 2026-04-24 Samuel Tiersma

In this article, we propose a new three parameter distribution by compounding negative binomial with reciprocal inverse Gaussian model called negative binomial-reciprocal inverse Gaussian distribution. This model is tractable with some…

Methodology · Statistics 2019-06-10 Ishfaq Shah Ahmad , Anwar Hassan , Peer Bilal Ahmad

We consider object allocation problems with capacities (see, e.g., Abdulkadiroglu and Sonmez, 1998; Basteck, 2025) where objects have to be assigned to agents. We show that if a lottery rule satisfies ex-post non-wastefulness and…

Theoretical Economics · Economics 2025-08-08 Tom Demeulemeester , Bettina Klaus

The main object of Bayesian statistical inference is the determination of posterior distributions. Sometimes these laws are given for quantities devoid of empirical value. This serious drawback vanishes when one confines oneself to…

Statistical Finance · Quantitative Finance 2008-12-02 Federico Bassetti

We propose new goodness-of-fit tests for the Pareto type I distribution. These tests are based on a multiplicative version of the memoryless property which characterises this distribution. We present the results of a Monte Carlo power study…

Methodology · Statistics 2024-01-26 Lethani Ndwandwe , James Allison , Leonard Santana , Jaco Visagie

If o and * are two binary operations in a number system, then three elements a,b,c in that number system are said to satisfy the distributive property of the operation o over the operation * if, ao(b*c)= (aob)*(aoc) Now, suppose that the…

General Mathematics · Mathematics 2009-06-17 Konstantine Zelator

Several probability distributions have been proposed in the literature, especially with the aim of obtaining models that are more flexible relative to the behaviors of the density and hazard rate functions. Recently, a new generalization of…

Computation · Statistics 2016-04-26 K. V. P. Barco , J. Mazucheli , V. Janeiro

Consider the problem where a statistician in a two-node system receives rate-limited information from a transmitter about marginal observations of a memoryless process generated from two possible distributions. Using its own observations,…

Information Theory · Computer Science 2017-03-02 Gil Katz , Pablo Piantanida , Mérouane Debbah

Associative memory and probabilistic modeling are two fundamental topics in artificial intelligence. The first studies recurrent neural networks designed to denoise, complete and retrieve data, whereas the second studies learning and…

Memory and forgetting constitute two sides of the same coin, and although the first has been rigorously investigated, the latter is often overlooked. A number of experiments under the realm of psychology and experimental neuroscience have…

Neurons and Cognition · Quantitative Biology 2019-07-23 Antonios Georgiou , Mikhail Katkov , Misha Tsodyks

The notion of probability plays an important role in almost all areas of science and technology. In modern mathematics, however, probability theory means nothing other than measure theory, and the operational characterization of the notion…

Probability · Mathematics 2019-09-09 Kohtaro Tadaki

A probabilistic query may not be estimable from observed data corrupted by missing values if the data are not missing at random (MAR). It is therefore of theoretical interest and practical importance to determine in principle whether a…

Machine Learning · Statistics 2016-11-16 Jin Tian

The power prior is a class of informative priors designed to incorporate historical data alongside current data in a Bayesian framework. It includes a power parameter that controls the influence of historical data, providing flexibility and…

Machine Learning · Statistics 2025-05-23 Masanari Kimura , Howard Bondell

In many data analyses, each measurement may come with a simple yes/no correction; for example, belonging to one of two populations or being contaminated or not. Ignoring such binary effects may bias the results, while accounting for them…

Cosmology and Nongalactic Astrophysics · Physics 2026-05-13 Marcus Högås , Edvard Mörtsell

This study proposes a new efficiency requirement, a minimal almost weak Pareto principle, which says that x is socially better than y whenever the only one individual never prefers y to x, and all the others prefers x to y. Then, I show…

Theoretical Economics · Economics 2025-01-20 Norihito Sakamoto

Associative memories are structures that store data in such a way that it can later be retrieved given only a part of its content -- a sort-of error/erasure-resilience property. They are used in applications ranging from caches and memory…

Information Theory · Computer Science 2013-04-23 Vincent Gripon , Michael Rabbat

We show a cancellation property for probabilistic choice. If distributions mu + rho and nu + rho are branching probabilistic bisimilar, then distributions mu and nu are also branching probabilistic bisimilar. We do this in the setting of a…

Logic in Computer Science · Computer Science 2023-09-15 Rob van Glabbeek , Jan Friso Groote , Erik de Vink