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We introduce a protocol addressing the conformance test problem, which consists in determining whether a process under test conforms to a reference one. We consider a process to be characterized by the set of end-product it produces, which…

This survey gives a comprehensive account of quantum correlations understood as a phenomenon stemming from the rules of quantization. Centered on quantum probability it describes the physical concepts related to correlations (both classical…

Quantum Physics · Physics 2015-05-22 W. A. Majewski

The development of large databases of material properties, together with the availability of powerful computers, has allowed machine learning (ML) modeling to become a widely used tool for predicting material performances. While confidence…

Materials Science · Physics 2023-10-23 Francesca Tavazza , Kamal Choudhary , Brian DeCost

The field of property testing of probability distributions, or distribution testing, aims to provide fast and (most likely) correct answers to questions pertaining to specific aspects of very large datasets. In this work, we consider a…

Data Structures and Algorithms · Computer Science 2015-04-27 Clément L. Canonne

We propose and study properties of maximum likelihood estimators in the class of conditional transformation models. Based on a suitable explicit parameterisation of the unconditional or conditional transformation function, we establish a…

Methodology · Statistics 2019-10-22 Torsten Hothorn , Lisa Möst , Peter Bühlmann

Quantum probabilities are defined for several important physical cases characterizing measurements with multimode quantum systems. These are the probabilities for operationally testable measurements, for operationally uncertain…

Quantum Physics · Physics 2015-06-19 V. I. Yukalov , E. P. Yukalova , D. Sornette

In real supervised learning scenarios, it is not uncommon that the training and test sample follow different probability distributions, thus rendering the necessity to correct the sampling bias. Focusing on a particular covariate shift…

Machine Learning · Computer Science 2012-06-22 Yaoliang Yu , Csaba Szepesvari

The new interpretation of Quantum Mechanics is based on a complex probability theory. An interpretation postulate specifies events which can be observed and it follows that the complex probability of such event is, in fact, a real positive…

Quantum Physics · Physics 2007-05-23 Jiri Soucek

This essay is an attempted to address, from a modern perspective, the motion of a particle. Quantum mechanically, motion consists of a series of localizations due to repeated interactions that, taken close to the limit of the continuum,…

General Physics · Physics 2015-05-14 Gerald E. Marsh

A rigorous general definition of quantum probability is given, which is valid for elementary events and for composite events, for operationally testable measurements as well as for inconclusive measurements, and also for non-commuting…

Quantum Physics · Physics 2016-01-12 V. I. Yukalov , D. Sornette

Information theory is built on probability measures and by definition a probability measure has total mass 1. Probability measures are used to model uncertainty, and one may ask how important it is that the total mass is one. We claim that…

Information Theory · Computer Science 2022-02-08 Peter Harremoës

Quantile regression is a powerful tool for inferring how covariates affect specific percentiles of the response distribution. Existing methods either estimate conditional quantiles separately for each quantile of interest or estimate the…

Methodology · Statistics 2024-11-19 Joseph Feldman , Daniel Kowal

In quantum operations, probabilities characterise both the degree of the success of a state transformation and, as density operator eigenvalues, the degree of mixedness of the final state. We give a unified treatment of pure-to-pure state…

Quantum Physics · Physics 2009-11-07 Anthony Chefles

Uncertainty quantification is an important part of many performance critical applications. This paper provides a simple alternative to existing approaches such as ensemble learning and bayesian neural networks. By directly modeling the loss…

Machine Learning · Computer Science 2024-08-28 Yi Hung Lim

Empirical likelihood approach is one of non-parametric statistical methods, which is applied to the hypothesis testing or construction of confidence regions for pivotal unknown quantities. This method has been applied to the case of…

Statistics Theory · Mathematics 2015-09-21 Fumiya Akashi , Yan Liu , Masanobu Taniguchi

The Box-Cox transformation is applied to the linear mixed models for analyzing positive and grouped data. The problem in using Box Cox transformation is that the maximum likelihood estimator of the transformation parameter is generally…

Methodology · Statistics 2016-09-07 Shonosuke Sugasawa , Tatsuya Kubokawa

Quantile is an important risk measure quantifying the stochastic system random behaviors. This paper studies a pooled quantile estimator, which is the sample quantile of detailed simulation outputs after directly pooling independent sample…

Methodology · Statistics 2019-10-15 Qiong Zhang , Bo Wang , Wei Xie

Teleportation may be taken as sending and extracting quantum information through quantum channels. In this report, it is shown that to get the maximal probability of exact teleportation through partially entangled quantum channels, the…

Quantum Physics · Physics 2009-10-31 Wan-Li Li , Chuan-Feng Li , Guang-Can Guo

In classical statistical decision theory, comparison of experiments plays very important role. Especially, so-called randomization criteria is most important. In this paper, we establish two kinds of quantum analogue these concepts, and…

Quantum Physics · Physics 2015-05-20 Keiji Matsumoto

The relational interpretation (or RQM, for Relational Quantum Mechanics) solves the measurement problem by considering an ontology of sparse relative events, or "facts". Facts are realized in interactions between any two physical systems…

Quantum Physics · Physics 2021-10-04 Carlo Rovelli
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