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We introduce quantitative and robust tools to control the numerical accuracy in simulations performed using the Multiscale Finite Element Method (MsFEM). First, we propose a guaranteed and fully computable a posteriori error estimate for…

Numerical Analysis · Mathematics 2018-05-09 Ludovic Chamoin , Frederic Legoll

We present two practical improvement techniques for unsupervised segmentation learning. These techniques address limitations in the resolution and accuracy of predicted segmentation maps of recent state-of-the-art methods. Firstly, we…

Computer Vision and Pattern Recognition · Computer Science 2024-12-02 Alp Eren Sari , Francesco Locatello , Paolo Favaro

Many applications require the collection of data on different variables or measurements over many system performance metrics. We term those broadly as measures or variables. Often data collection along each measure incurs a cost, thus it is…

Methodology · Statistics 2021-11-30 Donghui Yan , Zhiwei Qin , Songxiang Gu , Haiping Xu , Ming Shao

We explore fairness from a statistical perspective by selectively utilizing either conditional distance covariance or distance covariance statistics as measures to assess the independence between predictions and sensitive attributes. We…

Machine Learning · Computer Science 2025-12-22 Ruifan Huang , Haixia Liu

A common goal in observational research is to estimate marginal causal effects in the presence of confounding variables. One solution to this problem is to use the covariate distribution to weight the outcomes such that the data appear…

Methodology · Statistics 2020-08-18 Kevin P. Josey , Elizabeth Juarez-Colunga , Fan Yang , Debashis Ghosh

Machine-learning models are ubiquitous. In some domains, for instance, in medicine, the models' predictions must be interpretable. Decision trees, classification rules, and subgroup discovery are three broad categories of supervised…

Machine Learning · Computer Science 2022-04-29 Vadim Arzamasov , Benjamin Jochum , Klemens Böhm

Market-based mechanisms such as auctions are being studied as an appropriate means for resource allocation in distributed and mulitagent decision problems. When agents value resources in combination rather than in isolation, they must often…

Artificial Intelligence · Computer Science 2013-01-30 Craig Boutilier , Moises Goldszmidt , Bikash Sabata

Mixed membership models, or partial membership models, are a flexible unsupervised learning method that allows each observation to belong to multiple clusters. In this paper, we propose a Bayesian mixed membership model for functional data.…

The stochastic nature of chemical reactions involving randomly fluctuating population sizes has lead to a growing research interest in discrete-state stochastic models and their analysis. A widely-used approach is the description of the…

Quantitative Methods · Quantitative Biology 2015-10-01 Alexander Andreychenko , Luca Bortolussi , Ramon Grima , Philipp Thomas , Verena Wolf

This paper builds on recent research that focuses on regression modeling of continuous bounded data, such as proportions measured on a continuous scale. Specifically, it deals with beta regression models with mixed effects from a Bayesian…

Several authors have recently developed risk-sensitive policy gradient methods that augment the standard expected cost minimization problem with a measure of variability in cost. These studies have focused on specific risk-measures, such as…

Artificial Intelligence · Computer Science 2015-06-09 Aviv Tamar , Yinlam Chow , Mohammad Ghavamzadeh , Shie Mannor

We study proportional representation in the temporal voting model, where collective decisions are made repeatedly over time over a fixed horizon. Prior work has extensively investigated how proportional representation axioms from…

Computer Science and Game Theory · Computer Science 2026-05-13 Nicholas Teh

In this paper, a quantitative measure of partial observability is defined for PDEs. The quantity is proved to be consistent if the PDE is approximated using well-posed approximation schemes. A first order approximation of an unobservability…

Optimization and Control · Mathematics 2014-01-03 Wei Kang , Liang Xu , Francis X. Giraldo

Fairness in machine learning is predominantly evaluated through outcome-oriented metrics, such as Demographic parity, which measure whether predictions are statistically consistent across protected groups. However, these metrics cannot…

Artificial Intelligence · Computer Science 2026-05-18 Gideon Popoola , John Sheppard

In this paper, we empirically investigate correlations among four centrality measures, originated from the social science, of various complex networks. For each network, we compute the centrality measures, from which the partial correlation…

Physics and Society · Physics 2007-05-23 Chang-Yong Lee

Recently, a proposal has been advanced to detect unconstitutional partisan gerrymandering with a simple formula called the efficiency gap. The efficiency gap is now working its way towards a possible landmark case in the Supreme Court. This…

Physics and Society · Physics 2017-06-01 Mira Bernstein , Moon Duchin

We study equivalence, in the context of a variable diffusion problem, between (conforming) mixed methods and (primal) nonconforming methods defined on potentially general polytopal partitions. In this first paper of a series of two, we…

Numerical Analysis · Mathematics 2026-02-18 Simon Lemaire

A two-level quantum system evolving under a time-independent Hamiltonian produces oscillatory measurement probabilities. The estimation of the associated frequency is a cornerstone problem in quantum metrology, sensing, calibration and…

Quantum Physics · Physics 2025-08-12 Alexandra Ramôa , Luís Paulo Santos , Akihito Soeda

In pattern mining, sequential rules provide a formal framework to capture the temporal relationships and inferential dependencies between items. However, the discovery process is computationally intensive. To obtain mining results…

Databases · Computer Science 2026-02-20 Wensheng Gan , Gengsen Huang , Junyu Ren , Philip S. Yu

The increasing growth of databases raises an urgent need for more accurate methods to better understand the stored data. In this scope, association rules were extensively used for the analysis and the comprehension of huge amounts of data.…

Databases · Computer Science 2013-05-27 Slim Bouker , Rabie Saidi , Sadok Ben Yahia , Engelbert Mephu Nguifo