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Related papers: On weighted failure rate, its means and associated…

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Measure of the weighted cumulative entropy about the predictability of failure time of a system have been introduced in [3]. Referring properties of doubly truncated (interval) cumulative residual and past entropy, several bounds and…

Information Theory · Computer Science 2015-08-28 Salimeh Yasaei Sekeh , Gholamreza Mohtashami Borzadran , Abdolhamid Rezaei Roknabadi

Failure Mode Reasoning (FMR) is a method for formal analysis of system-related faults. The method was originally developed for identifying failure modes of safety-critical systems based on an analysis of their programs. In this paper, we…

Software Engineering · Computer Science 2022-10-18 Hamid Jahanian

As a model of composite material, the fiber bundle model has been chosen -where a bundle of fibers is subjected to external load and fibers have distributed thresholds. For different loading conditions, such a system shows few precursors…

Materials Science · Physics 2015-05-19 Srutarshi Pradhan

In the multiple linear regression setting, we propose a general framework, termed weighted orthogonal components regression (WOCR), which encompasses many known methods as special cases, including ridge regression and principal components…

Machine Learning · Statistics 2018-01-24 Xiaogang Su , Yaa Wonkye , Pei Wang , Xiangrong Yin

Weighted model counting (WMC) consists of computing the weighted sum of all satisfying assignments of a propositional formula. WMC is well-known to be #P-hard for exact solving, but admits a fully polynomial randomized approximation scheme…

Artificial Intelligence · Computer Science 2020-07-14 Ralph Abboud , İsmail İlkan Ceylan , Radoslav Dimitrov

We introduce and investigate a weighted propositional configuration logic over commutative semirings. Our logic is intended to serve as a specification language for software architectures with quantitative features. We prove an efficient…

Logic in Computer Science · Computer Science 2020-01-20 Paulina Paraponiari , George Rahonis

The generalization capacity of various machine learning models exhibits different phenomena in the under- and over-parameterized regimes. In this paper, we focus on regression models such as feature regression and kernel regression and…

Machine Learning · Computer Science 2022-03-14 Björn Engquist , Kui Ren , Yunan Yang

In recent years, various phase field models have been developed in variational methods to simulate the failure of brittle solids. However, there is a lack of objective evaluation of the existing results, and in particular, there are few…

Numerical Analysis · Mathematics 2021-09-23 Yuanfeng Yu , Xiaoya Zheng , Peng Li , Zhongzhou Zhang , Jinyou Xiao

We propose a class of flexible non-parametric tests for the presence of dependence between components of a random vector based on weighted Cram\'{e}r-von Mises functionals of the empirical copula process. The weights act as a tuning…

Statistics Theory · Mathematics 2014-05-29 Ivan Medovikov

When machine learning supports decision-making in safety-critical systems, it is important to verify and understand the reasons why a particular output is produced. Although feature importance calculation approaches assist in…

Machine Learning · Statistics 2020-09-14 Divish Rengasamy , Benjamin Rothwell , Grazziela Figueredo

We consider sequences of integers defined by a system of linear inequalities with integer coefficients. We show that when the constraints are strong enough to guarantee that all the entries are nonnegative, the generating function for the…

Combinatorics · Mathematics 2007-05-23 S. Corteel , C. D. Savage

We compare the notions "Decisiveness" and "Success" for certain weighted voting systems and various underlying voting measures. In particular, we compute the success rate for the Shapley-Shubik meassure and, more generally, for Common…

General Mathematics · Mathematics 2017-06-27 Werner Kirsch

We describe Fibres of Failure (FiFa), a method to classify failure modes of predictive processes using the Mapper algorithm from Topological Data Analysis. Our method uses Mapper to build a graph model of input data stratified by prediction…

Computer Vision and Pattern Recognition · Computer Science 2018-03-02 Leo Carlsson , Gunnar Carlsson , Mikael Vejdemo-Johansson

Errors in variables (Deming) regression of measurements spanning a wide range of values requires appropriate weighting to reflect nonconstant variance. Precision profile models, mathematical relationships between measurement variance and…

Computation · Statistics 2025-08-06 Douglas M Hawkins , Jessica J Kraker

We describe here a framework for a certain class of multiscale likelihood factorizations wherein, in analogy to a wavelet decomposition of an L^2 function, a given likelihood function has an alternative representation as a product of…

Statistics Theory · Mathematics 2007-06-13 Eric D. Kolaczyk , Robert D. Nowak

We propose three novel consistent specification tests for quantile regression models which generalize former tests in three ways. First, we allow the covariate effects to be quantile-dependent and nonlinear. Second, we allow parameterizing…

Methodology · Statistics 2021-12-07 Tim Kutzker , Nadja Klein , Dominik Wied

Quantum finite automata derive their strength by exploiting interference in complex valued probability amplitudes. Of particular interest is the 2-way model of Ambainis and Watrous that has both quantum and classical states (2QCFA) [A.…

Quantum Physics · Physics 2007-05-23 M. V. Panduranga Rao , V. Vinay

Items in a test are often used as a basis for making decisions and such tests are therefore required to have good psychometric properties, like unidimensionality. In many cases the sum score is used in combination with a threshold to decide…

Methodology · Statistics 2020-07-14 Lourens Waldorp , Maarten Marsman , Denny Borsboom

In this article, we present weighted norm inequality for a fractional one-sided minimal function. We prove weighted weak and strong type norm inequalities for the one-sided minimal function on $\mathbb{R}.$ We construct two weight classes…

Classical Analysis and ODEs · Mathematics 2020-02-06 Duranta Chutia , Rajib Haloi

Overparameterized models that achieve zero training error are observed to generalize well on average, but degrade in performance when faced with data that is under-represented in the training sample. In this work, we study an…

Machine Learning · Statistics 2024-05-13 Kuo-Wei Lai , Vidya Muthukumar