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Related papers: $\epsilon'/\epsilon$: three years later

200 papers

Confirmation bias is a cognitive bias that adversely affects management decisions, and mathematical modelling is an aid to its detailed understanding. Bias in opinion update about the value of a parameter is modelled here assuming that…

Other Statistics · Statistics 2022-02-08 Rose D Baker

Traditionally, Probability theory was dealing with limit theorems where 'limit" means that time tends to infinity. Questions about finite time dynamics (evolution) were always considered as, although important for practical applications,…

Chaotic Dynamics · Physics 2025-12-19 Leonid Bunimovich , Kirill Kovalenko

Statistical significance measures the reliability of a result obtained from a random experiment. We investigate the number of repetitions needed for a statistical result to have a certain significance. In the first step, we consider…

Methodology · Statistics 2024-06-19 Maike Tormählen , Galiya Klinkova , Michael Grabinski

Recent tentative experimental indications, and the subsequent theoretical speculations, regarding possible violations of Lorentz invariance have attracted a vast amount of attention. An important technical issue that considerably…

High Energy Physics - Phenomenology · Physics 2017-11-29 Valentina Baccetti , Kyle Tate , Matt Visser

Counts in cells are used to analyse the higher order properties of the statistics of the EDSGC survey. The probability distribution is obtained from an equal area projection source catalog with infinite oversampling over the range…

Astrophysics · Physics 2009-10-28 István Szapudi , Avery Meiksin , Robert C. Nichol

Within the last few years, there has been a move towards using statistical models in conjunction with neural networks with the end goal of being able to better answer the question, "what do our models know?". From this trend, classical…

Machine Learning · Computer Science 2021-12-03 Achintya Gopal

The aim of this paper is to discuss both higher-order asymptotic expansions and skewed approximations for the Bayesian Discrepancy Measure for testing precise statistical hypotheses. In particular, we derive results on third-order…

Methodology · Statistics 2025-05-02 Elena Bortolato , Francesco Bertolino , Monica Musio , Laura Ventura

The Cepheids' P-L relation got itself talked about again in the recent past due to claims of observed metallicity dependences of at least its zero point. The divergences of the observational results obtained by the different authors are…

Astrophysics · Physics 2007-05-23 Alfred Gautschy

The Rashomon Effect describes the following phenomenon: for a given dataset there may exist many models with equally good performance but with different solution strategies. The Rashomon Effect has implications for Explainable Machine…

Machine Learning · Computer Science 2023-06-30 Sebastian Müller , Vanessa Toborek , Katharina Beckh , Matthias Jakobs , Christian Bauckhage , Pascal Welke

We present the results of our recent calculation of $\epsilon^{\prime}/ \epsilon$ at the Next-to-Leading (NLO) order in QCD and QED, in the framework of $\DSone$ Effective Hamiltonians. The operator matrix elements are taken from lattice…

High Energy Physics - Phenomenology · Physics 2007-05-23 L. Reina

We consider list versions of sparse approximation problems, where unlike the existing results in sparse approximation that consider situations with unique solutions, we are interested in multiple solutions. We introduce these problems and…

Information Theory · Computer Science 2014-08-12 Mahmoud Abo Khamis , Anna C. Gilbert , Hung Q. Ngo , Atri Rudra

Let $(P,\leq)$ be a finite poset (partially ordered set), where $P$ has cardinality $n$. Consider linear extensions of $P$ as permutations $x_1x_2\cdots x_n$ in one-line notation. For distinct elements $x,y\in P$, we define…

Combinatorics · Mathematics 2018-02-02 Emily J. Olson , Bruce E. Sagan

We propose a rigorous decomposition of predictive error, highlighting that not all 'irreducible' error is genuinely immutable. Many domains stand to benefit from iterative enhancements in measurement, construct validity, and modeling. Our…

Machine Learning · Computer Science 2025-02-12 Jiani Yan , Charles Rahal

Inspired by the context of compressing encrypted sources, this paper considers the general tradeoff between rate, end-to-end delay, and probability of error for lossless source coding with side-information. The notion of end-to-end delay is…

Information Theory · Computer Science 2007-12-07 Cheng Chang , Anant Sahai

The points at which the log likelihood falls by 1/2 from its maximum value are often used to give the `errors' on a result, i.e. the 68% central confidence interval. The validity of this is examined for two simple cases: a lifetime…

Data Analysis, Statistics and Probability · Physics 2007-05-23 Roger Barlow

The physics of high-energy collider experiments asks for delicate comparisons between theoretical predictions and experimental data. Signals and potential backgrounds for new physics have to be predicted at sufficient accuracy. The accuracy…

High Energy Physics - Phenomenology · Physics 2007-05-23 A. van Hameren , C. G. Papadopoulos

This review aims to provide a comprehensive update on the progress made on the Sequential Testing problem (STP) in the last 20 years after the review, [1] was published. Many studies have provided new theoretical results, extensions of the…

Data Structures and Algorithms · Computer Science 2025-11-21 Tonguç Ünlüyurt

When searching for a new resonance somewhere in a possible mass range, the significance of observing a local excess of events must take into account the probability of observing such an excess anywhere in the range. This is the so called…

Data Analysis, Statistics and Probability · Physics 2015-03-17 Eilam Gross , Ofer Vitells

In order to make quantitative predictions for jet cross sections in perturbative QCD, it is essential to calculate them to next-to-leading accuracy. This has traditionally been an extremely laborious process. Using a new formalism,…

High Energy Physics - Phenomenology · Physics 2009-10-28 Stefano Catani , Michael H. Seymour

When the historical data are limited, the conditional probabilities associated with the nodes of Bayesian networks are uncertain and can be empirically estimated. Second order estimation methods provide a framework for both estimating the…

Machine Learning · Statistics 2022-08-09 Conrad D. Hougen , Lance M. Kaplan , Federico Cerutti , Alfred O. Hero