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The demand for global university league tables has been high over the past two decades. However, significant criticism of their methodologies is accumulating without being addressed. I revisit global university league tables by normalizing…

Physics and Society · Physics 2023-08-22 Saulo Mendes

The objective of the present study is to present a computational model of the motion of a single athlete in a team and to compare the resulting trajectory with experimental data obtained in the field during competitions by match analysis…

Biological Physics · Physics 2008-11-25 E. Grimpampi , A. Pasculli , A. Sacripanti

The typical central limit theorems in high-frequency asymptotics for semimartingales are results on stable convergence to a mixed normal limit with an unknown conditional variance. Estimating this conditional variance usually is a hard…

Probability · Mathematics 2020-03-25 Mathias Vetter

A quantum trajectory describes the evolution of a quantum system undergoing indirect measurement. In the discrete-time setting, the state of the system is updated by applying Kraus operators according to the measurement results. From an…

Quantum Physics · Physics 2022-04-04 Maël Bompais , Nina H. Amini , Clément Pellegrini

In sequential change detection, existing performance measures differ significantly in the way they treat the time of change. By modeling this quantity as a random time, we introduce a general framework capable of capturing and better…

Statistics Theory · Mathematics 2008-12-18 George V. Moustakides

Evaluating sports players based on their performance shares core challenges with evaluating healthcare providers based on patient outcomes. Drawing on recent advances in healthcare provider profiling, we cast sports player evaluation within…

Applications · Statistics 2026-02-27 Herbert P. Susmann , Antonio D'Alessandro

Humans perform exquisite sensorimotor skills, both individually and in teams, from athletes performing rhythmic gymnastics to everyday tasks like carrying a cup of coffee. The "predictive brain" framework suggests that mastering these…

Neurons and Cognition · Quantitative Biology 2025-03-10 Marta Russo , Antonella Maselli , Dagmar Sternad , Giovanni Pezzulo

A query performance predictor estimates the retrieval effectiveness of an IR system for a given query. An important characteristic of QPP evaluation is that, since the ground truth retrieval effectiveness for QPP evaluation can be measured…

Information Retrieval · Computer Science 2022-02-15 Debasis Ganguly , Suchana Datta , Mandar Mitra , Derek Greene

Differential privacy is a mathematical concept that provides an information-theoretic security guarantee. While differential privacy has emerged as a de facto standard for guaranteeing privacy in data sharing, the known mechanisms to…

Cryptography and Security · Computer Science 2024-03-26 March Boedihardjo , Thomas Strohmer , Roman Vershynin

A growing number of universities worldwide use various forms of online and blended learning as part of their academic curricula. Furthermore, the recent changes caused by the COVID-19 pandemic have led to a drastic increase in importance…

Machine Learning · Computer Science 2022-09-05 Galina Deeva , Johannes De Smedt , Cecilia Saint-Pierre , Richard Weber , Jochen De Weerdt

We design a recursive measure of voting power based on partial as well as full voting efficacy. Classical measures, by contrast, incorporate solely full efficacy. We motivate our design by representing voting games using a division lattice…

Theoretical Economics · Economics 2022-05-25 Arash Abizadeh , Adrian Vetta

Professional team sports provide an excellent domain for studying the dynamics of social competitions. These games are constructed with simple, well-defined rules and payoffs that admit a high-dimensional set of possible actions and…

Data Analysis, Statistics and Probability · Physics 2016-06-17 Leto Peel , Aaron Clauset

We study prediction-powered conditional inference in the setting where labeled data are scarce, unlabeled covariates are abundant, and a black-box machine-learning predictor is available. The goal is to perform statistical inference on…

Machine Learning · Statistics 2026-03-09 Yang Sui , Jin Zhou , Hua Zhou , Xiaowu Dai

In this paper we develop a complete analytical framework based on Random Matrix Theory for the performance evaluation of Eigenvalue-based Detection. While, up to now, analysis was limited to false-alarm probability, we have obtained an…

Information Theory · Computer Science 2009-09-23 Federico Penna , Roberto Garello

Humans are the final decision makers in critical tasks that involve ethical and legal concerns, ranging from recidivism prediction, to medical diagnosis, to fighting against fake news. Although machine learning models can sometimes achieve…

Artificial Intelligence · Computer Science 2019-01-10 Vivian Lai , Chenhao Tan

Power law or generalized polynomial regressions with unknown real-valued exponents and coefficients, and weakly dependent errors, are considered for observations over time, space or space--time. Consistency and asymptotic normality of…

Statistics Theory · Mathematics 2012-05-14 Peter M. Robinson

Physics is a model of nature able to both describe and predict the results of measurements made with respect to reference systems. These reference systems, in turn, are themselves physical and thus subject to the laws of physics. The…

Quantum Physics · Physics 2025-09-05 Henrique A. R. Knopki , Renato M. Angelo

A rater's ability to assign accurate scores can significantly impact the outcomes of educational assessments. However, common indices for evaluating rater characteristics typically focus on either their severity or their discrimination…

Applications · Statistics 2025-02-14 Y. -G. Wang , J. Wu , X. Qiu

The work applies the funnel plot methodology to measure and visualize uncertainty in the research performance of Italian universities in the science disciplines. The performance assessment is carried out at both discipline and overall…

Digital Libraries · Computer Science 2018-10-31 Giovanni Abramo , Ciriaco Andrea D'Angelo , Leonardo Grilli

We study the performance of classical and quantum machine learning (ML) models in predicting outcomes of physical experiments. The experiments depend on an input parameter $x$ and involve execution of a (possibly unknown) quantum process…

Quantum Physics · Physics 2021-05-19 Hsin-Yuan Huang , Richard Kueng , John Preskill