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The term "measurement" in quantum theory (as well as in other physical theories) is ambiguous: It is used to describe both an experience - e.g., an observation in an experiment - and an interaction with the system under scrutiny. If doing…

Quantum Physics · Physics 2019-04-03 Arne Hansen , Stefan Wolf

How can one meaningfully make a measurement, if the meter does not conform to any standard and its scale expands or shrinks depending on what is measured? In the present work it is argued that current evaluation practices for…

Machine Learning · Computer Science 2023-02-24 K. Dyrland , A. S. Lundervold , P. G. L. Porta Mana

Technology applied in education can provide great benefits and overcome challenges by facilitating access to learning objects anywhere and anytime. However, technology alone is not enough, since it requires suitable planning and learning…

Computers and Society · Computer Science 2022-09-26 Gabriel Leitão , Juan Colonna , Edwin Monteiro , Elaine Oliveira , Raimundo Barreto

Let X be a non-empty set and U a ring of subsets of X. The countable additive functions U->{0,1} are called measures. The paper gives some definitions (derivable measures, the Lebesgue-Stieltjes measures) and properties of these functions,…

General Mathematics · Mathematics 2007-05-23 Serban E. Vlad

Educational guide focused on the statistical treatment of measurement uncertainties. The conditions of application of current practices are detailed and precised: mean values, central limit theorem, linear regression. The last two chapters…

Other Statistics · Statistics 2020-07-15 Romain Legrand

Measure and integral are two closely related, but distinct objects of study. Nonetheless, they are both real-valued lattice valuations: order preserving real-valued functions $\phi$ on a lattice $L$ which are modular, i.e.,…

Functional Analysis · Mathematics 2019-03-15 Abraham A. Westerbaan

The application of machine learning to physics problems is widely found in the scientific literature. Both regression and classification problems are addressed by a large array of techniques that involve learning algorithms. Unfortunately,…

Machine Learning · Computer Science 2022-10-03 Umberto Michelucci , Francesca Venturini

Mobile applications and other integration of information and communication technology (ICT) have become well-known in education to monitor teaching and learning activities. The analysis of student learning through evaluation is a growing…

Human-Computer Interaction · Computer Science 2022-02-08 Ronel B. Dayanghirang , Alexander A. Hernandez

These series of notes serve as an introduction to some of both the classical and modern techniques in Reifenberg theory. At its heart, Reifenberg theory is about studying general sets or measures which can be, in one sense or another,…

Analysis of PDEs · Mathematics 2018-12-19 Aaron Naber

These few pages briefly present the way in which Activity Theory has been adopted for several years now by French researchers in didactics of mathematics and has been adapted to study the learning of school mathematics in relation with the…

Physics Education · Physics 2019-05-08 Maha Abboud-Blanchard , Aline Robert , Janine Rogalski , Fabrice Vandebrouck

Feedback on student answers and even during intermediate steps in their solutions to open-ended questions is an important element in math education. Such feedback can help students correct their errors and ultimately lead to improved…

Machine Learning · Computer Science 2021-04-27 Mengxue Zhang , Zichao Wang , Richard Baraniuk , Andrew Lan

Information theory is a powerful framework for quantifying complexity, uncertainty, and dynamical structure in time-series data, with widespread applicability across disciplines such as physics, finance, and neuroscience. However, the…

Information Theory · Computer Science 2026-01-26 Annie G. Bryant , Oliver M. Cliff , James M. Shine , Ben D. Fulcher , Joseph T. Lizier

We consider a distributed learning setting where each agent/learner holds a specific parametric model and data source. The goal is to integrate information across a set of learners to enhance the prediction accuracy of a given learner. A…

Methodology · Statistics 2021-09-21 Jiaying Zhou , Jie Ding , Kean Ming Tan , Vahid Tarokh

We introduce a notion of integration defined from filters over families of finite sets. This procedure corresponds to determining the average value of functions whose range lies in any algebraic structure in which finite averages make…

Logic · Mathematics 2021-08-27 Emanuele Bottazzi , Monroe Eskew

Nonlinear models and optimization methods have successfully tackled a rapidly growing set of problems in recent years. Indeed, a relatively small toolbox of such models and methods can provide sufficient performance across a large landscape…

Optimization and Control · Mathematics 2026-05-01 Akshunna S. Dogra

As learning difficulty is crucial for machine learning (e.g., difficulty-based weighting learning strategies), previous literature has proposed a number of learning difficulty measures. However, no comprehensive investigation for learning…

Machine Learning · Computer Science 2022-09-20 Weiyao Zhu , Ou Wu , Fengguang Su , Yingjun Deng

Let $X$ be a complete measure space of finite measure. The Lebesgue transform of an integrable function $f$ on $X$ encodes the collection of all the mean-values of $f$ on all measurable subsets of $X$ of positive measure. In the problem of…

Functional Analysis · Mathematics 2024-07-26 Fausto Di Biase , Steven G. Krantz

No consensus seems to exist as to what constitutes a measurement which is still considered somewhat mysterious in many respects in quantum mechanics. At successive stages mathematical theory of measure, metrology and measurement theory…

Quantum Physics · Physics 2008-11-21 Paolo Rocchi , Orlando Panella

Information geometry is used to quantify the amount of information integration within multiple terminals of a causal dynamical system. Integrated information quantifies how much information is lost when a system is split into parts and…

Information Theory · Computer Science 2017-09-08 Shun-ichi Amari , Naotsugu Tsuchiya , Masafumi Oizumi

We introduce a class of information measures based on group entropies, allowing us to describe the information-theoretical properties of complex systems. These entropic measures are nonadditive, and are mathematically deduced from a series…

Statistical Mechanics · Physics 2019-10-21 Piergiulio Tempesta , Henrik Jeldtoft Jensen