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Related papers: An annotated bibliography for comparative prime nu…

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We present a detailed proof of the prime number theorem suitable for a typical undergraduate- or graduate-level complex analysis course. Our presentation is particularly useful for any instructor who seeks to use the prime number theorem…

History and Overview · Mathematics 2021-02-05 Stephan Ramon Garcia

Information Extraction is a well-researched area of Natural Language Processing with applications in web search and question answering concerned with identifying entities and relationships between them as expressed in a given context,…

Information Retrieval · Computer Science 2020-11-17 Erin Macdonald , Denilson Barbosa

The combinatorial theory for the set of parity alternating permutations is expounded. In view of the numbers of ascents and inversions, several enumerative aspects of the set are investigated. In particular, it is shown that signed Eulerian…

Combinatorics · Mathematics 2017-06-13 Shinji Tanimoto

The presented work proposes a novel approach to model the citation rate. The paper begins with a brief introduction into informetrics studies and highlights drawbacks of the contemporary approaches to modeling the citation process as a…

Digital Libraries · Computer Science 2007-05-23 V. V. Kryssanov , F. J. Rinaldo , H. Ogawa , E. Kuleshov

This paper presents a type theory with a form of equality reflection: provable equalities can be used to coerce the type of a term. Coercions and other annotations, including implicit arguments, are dropped during reduction of terms. We…

Programming Languages · Computer Science 2011-01-25 Vilhelm Sjöberg , Aaron Stump

Even though data annotation is extremely important for interpretability, research and development of artificial intelligence solutions, most research efforts such as active learning or few-shot learning focus on the sample efficiency…

Machine Learning · Computer Science 2023-07-06 Franco Marchesoni-Acland , Jean-Michel Morel , Josselin Kherroubi , Gabriele Facciolo

In this short paper, following the most recent advances in complex network theory, a new approach to number theory with potential applications to other fields is proposed. The model by Garcia-Perez, Serrano and Boguna, introduces an…

Physics and Society · Physics 2014-10-06 Daniele Vilone

This work in progress aims to provide a unified introduction to statistical learning, building up slowly from classical models like the GMM and HMM to modern neural networks like the VAE and diffusion models. There are today many internet…

Machine Learning · Computer Science 2025-07-31 Joseph G. Makin

The aim of this research is twofold: Firstly, to model and solve a complex nurse scheduling problem with an integer programming formulation and evolutionary algorithms. Secondly, to detail a novel statistical method of comparing and hence…

Neural and Evolutionary Computing · Computer Science 2010-07-05 Uwe Aickelin , Paul White

Classification is an important goal in many branches of mathematics. The idea is to describe the members of some class of mathematical objects, up to isomorphism or other important equivalence in terms of relatively simple invariants. Where…

Logic · Mathematics 2008-03-25 Wesley Calvert , Julia F. Knight

This paper provides both an introduction to and a detailed overview of the principles and practice of classifier calibration. A well-calibrated classifier correctly quantifies the level of uncertainty or confidence associated with its…

Machine Learning · Computer Science 2023-06-16 Telmo Silva Filho , Hao Song , Miquel Perello-Nieto , Raul Santos-Rodriguez , Meelis Kull , Peter Flach

We summarize the major results in number theory of the last decade.

History and Overview · Mathematics 2010-12-14 Adam Grygiel

In a context where most published articles are devoted to the development of "new methods", comparison studies are generally appreciated by readers but surprisingly given poor consideration by many scientific journals. In connection with…

Computation · Statistics 2015-06-11 Anne-Laure Boulesteix , Manuel J. A. Eugster

Inference and prediction are fundamental to the study of complex systems, where network data are often incomplete, inaccurate or obtained indirectly. In this paper, we review recent advances in network sampling and comparison, as well as in…

Statistical Mechanics · Physics 2025-12-09 Francisco A. Rodrigues

In an effort to assist factcheckers in the process of factchecking, we tackle the claim detection task, one of the necessary stages prior to determining the veracity of a claim. It consists of identifying the set of sentences, out of a long…

Computation and Language · Computer Science 2020-08-18 Lev Konstantinovskiy , Oliver Price , Mevan Babakar , Arkaitz Zubiaga

In this paper the preliminary results of a literature review on characteristics used to define continuous experiments are presented. In total 14 papers were selected. The results were synthesized into a model that gives an overview of all…

Software Engineering · Computer Science 2019-12-11 Florian Auer , Michael Felderer

We present an empirical comparison between two normalization mechanisms for citation-based indicators of research performance. These mechanisms aim to normalize citation counts for the field and the year in which a publication was…

Digital Libraries · Computer Science 2010-09-08 Ludo Waltman , Nees Jan van Eck , Thed N. van Leeuwen , Martijn S. Visser , Anthony F. J. van Raan

Citation metrics are becoming pervasive in the quantitative evaluation of scholars, journals and institutions. More then ever before, hiring, promotion, and funding decisions rely on a variety of impact metrics that cannot disentangle…

Digital Libraries · Computer Science 2015-09-03 Jasleen Kaur , Emilio Ferrara , Filippo Menczer , Alessandro Flammini , Filippo Radicchi

In this paper we present a phenomenological approach to describe a complex system: scientific research impact through Citation Mining. The novel concept of Citation Mining, a combination of citation bibliometrics and text mining, is used…

Physics and Society · Physics 2007-05-23 J. A del Rio , R. N. Kostoff , E. O. Garcia , A. M. Ramirez , J. A. Humenik

Conformal prediction has become increasingly popular for quantifying the uncertainty associated with machine learning models. Recent work in graph uncertainty quantification has built upon this approach for conformal graph prediction. The…

Machine Learning · Computer Science 2025-05-21 Pranav Maneriker , Aditya T. Vadlamani , Anutam Srinivasan , Yuntian He , Ali Payani , Srinivasan Parthasarathy
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