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Exploration has been a crucial part of reinforcement learning, yet several important questions concerning exploration efficiency are still not answered satisfactorily by existing analytical frameworks. These questions include exploration…

Machine Learning · Computer Science 2016-12-06 Liangpeng Zhang , Ke Tang , Xin Yao

The recent development of electric and electronic devices has been remarkable. The miniaturization of electronic devices and high integration are progressing by advances in mounting technology. As a result, the reliability of fatigue life…

Materials Science · Physics 2007-09-13 S. Kondo , Qiang Yu , T. Shibutani , M. Shiratori

To improve the reliability and efficiency of Web Software, the Testing Team should be creative and innovative. The experience and intuition of Tester also matters a lot and most often the destructive nature of Tester brings reliable…

Software Engineering · Computer Science 2019-03-05 Kamran Ali , Xia Xiaoling

Experimentation platforms in industry must often deal with customer trust issues. Platforms must prove the validity of their claims as well as catch issues that arise. As a central quantity estimated by experimentation platforms, the…

Methodology · Statistics 2025-11-21 Kedar Karhadkar , Jack Klys , Daniel Ting , Artem Vorozhtsov , Houssam Nassif

The paper illustrates an application of the Resampling approach [2] for the estimation of the aircraft circulation plan reliability. Resampling is an intensive computer statistical method, which can be used effectively in the case of small…

Applications · Statistics 2013-05-14 Maxim Fioshin

When a large body of data from diverse experiments is analyzed using a theoretical model with many parameters, the standard error matrix method and the general tools for evaluating errors may become inadequate. We present an iterative…

High Energy Physics - Phenomenology · Physics 2009-07-24 J. Pumplin , D. R. Stump , W. K. Tung

We establish a profound connection between coherent risk measures, a prominent object in quantitative finance, and uniform integrability, a fundamental concept in probability theory. Instead of working with absolute values of random…

Risk Management · Quantitative Finance 2025-04-08 Muqiao Huang , Ruodu Wang

In exploratory factor analysis, model parameters are usually estimated by maximum likelihood method. The maximum likelihood estimate is obtained by solving a complicated multivariate algebraic equation. Since the solution to the equation is…

Statistics Theory · Mathematics 2026-01-14 Ryoya Fukasaku , Kei Hirose , Yutaro Kabata , Keisuke Teramoto

To explain NLP models a popular approach is to use importance measures, such as attention, which inform input tokens are important for making a prediction. However, an open question is how well these explanations accurately reflect a…

Computation and Language · Computer Science 2022-11-02 Andreas Madsen , Nicholas Meade , Vaibhav Adlakha , Siva Reddy

Credibility theory provides tools to obtain better estimates by combining individual data with sample information. We apply the Credibility theory to a Uniform distribution that is used in testing the reliability of forecasting an interest…

Statistical Finance · Quantitative Finance 2014-09-18 Matteo Formenti

The model implied by factor score predictors does not reproduce the non-diagonal elements of the observed covariance matrix as well as the factor loadings. It is therefore investigated whether it is possible to estimate factor loadings for…

Applications · Statistics 2019-09-26 André Beauducel , Norbert Hilger

Many methods of estimating causal models do not provide estimates of confidence in the resulting model. In this work, a metric is proposed for validating the output of a causal model fit; the robustness of the model structure with resampled…

The article is devoted to the resampling approach application to the reliability problems. This approach to reliability problems was first proposed by Ivnitsky (1967). Resampling is intensive statistical computer method, which is…

Applications · Statistics 2013-04-25 Maxim Fioshin , Helen Fioshina

In this paper we focus on the problem of assigning uncertainties to single-point predictions. We introduce a cost function that encodes the trade-off between accuracy and reliability in probabilistic forecast. We derive analytic formula for…

Machine Learning · Statistics 2018-03-14 Enrico Camporeale

Nowadays, the consequences of failure and downtime of distributed systems have become more and more severe. As an obvious solution, these systems incorporate protection mechanisms to tolerate faults that could cause systems failures and…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-02-19 Andrey A. Shchurov , Radek Marik

Studies of the contextual and linguistic factors that constrain discourse phenomena such as reference are coming to depend increasingly on annotated language corpora. In preparing the corpora, it is important to evaluate the reliability of…

cmp-lg · Computer Science 2008-02-03 Rebecca J. Passonneau

One of the most important parts of cloud computing is storage devices, and Redundant Array of Independent Disks (RAID) systems are well known and frequently used storage devices. With the increasing production of data in cloud environments,…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-04-06 Leila Namvari-Tazehkand , Saeid Pashazadeh

The design of reliable circuits has received a lot of attention in the past, leading to the definition of several design techniques introducing fault detection and fault tolerance properties in systems for critical…

Hardware Architecture · Computer Science 2011-11-09 C. Bolchini , F. Salice , D. Sciuto , L. Pomante

We do the error analysis in reliability measures due to the assumption of independence amongst the component lifetimes. In reliability theory, we come across different n-component structures like series, parallel, and k-out-of-n systems. A…

Statistics Theory · Mathematics 2024-03-11 Subarna Bhattacharjee , Aninda K. Nanda , Subhasree Patra

The performance of learning models often deteriorates when deployed in out-of-sample environments. To ensure reliable deployment, we propose a stability evaluation criterion based on distributional perturbations. Conceptually, our stability…

Machine Learning · Statistics 2024-05-07 Jose Blanchet , Peng Cui , Jiajin Li , Jiashuo Liu
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