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Statistical thinking partially depends upon an iterative process by which essential features of a problem setting are identified and mapped onto an abstract model or archetype, and then translated back into the context of the original…

Other Statistics · Statistics 2019-02-21 Matthew Beckman , Robert delMas

This paper summarises our work on studying educational applications enabled by the introduction of a new information layer called InfoInternet. This is an initiative to facilitate affordable access to internet based information in…

Computers and Society · Computer Science 2023-08-17 Johanna Johansen , Christian Johansen , Josef Noll

Mobile devices such as smartphones and tablets have become ubiquitous in today's modern computing landscape. The applications that run on these mobile devices (often referred to as "apps") have become a primary means of computing for…

Software Engineering · Computer Science 2018-07-20 Kevin Moran

Simulation studies are computer experiments that involve creating data by pseudorandom sampling. The key strength of simulation studies is the ability to understand the behaviour of statistical methods because some 'truth' (usually some…

Methodology · Statistics 2019-01-18 Tim P Morris , Ian R White , Michael J Crowther

With the aim of finding ways that can lead to solving the problem of learning the exact sciences and involving the university student in a participatory and active way during the semester period with the help of new technologies, the…

Physics Education · Physics 2023-08-17 Guillermo Jose Navarro del Toro

Now-a-days the amount of data stored in educational database increasing rapidly. These databases contain hidden information for improvement of students' performance. Educational data mining is used to study the data available in the…

Machine Learning · Computer Science 2012-03-20 Surjeet Kumar Yadav , Saurabh Pal

Interactive simulation toolkits come in handy when teaching macroeconomic models by facilitating an easy understanding of underlying economic concepts and offering an intuitive approach to the models' comparative statics. Based on the…

General Finance · Quantitative Finance 2020-08-07 Juan Dominguez-Moran , Rouven Geismar

We consider the problem of online active learning to collect data for regression modeling. Specifically, we consider a decision maker with a limited experimentation budget who must efficiently learn an underlying linear population model.…

Machine Learning · Statistics 2016-12-22 Carlos Riquelme , Ramesh Johari , Baosen Zhang

This thesis explores a number of online machine learning algorithms. From a theoret- ical perspective, it assesses their employability for a particular function approximation problem where the analytical models fall short. Furthermore, it…

Machine Learning · Computer Science 2016-05-04 Ahmet Anil Pala

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

The growth of world-wide-web (WWW) spreads its wings from an intangible quantities of web-pages to a gigantic hub of web information which gradually increases the complexity of crawling process in a search engine. A search engine handles a…

Information Retrieval · Computer Science 2012-08-14 Sudarshan Nandy , Partha Pratim Sarkar , Achintya Das

We present statistical methods for big data arising from online analytical processing, where large amounts of data arrive in streams and require fast analysis without storage/access to the historical data. In particular, we develop…

Computation · Statistics 2018-06-13 Elizabeth D. Schifano , Jing Wu , Chun Wang , Jun Yan , Ming-Hui Chen

The objective of this work is the investigation of complexity, asymmetry, stochasticity and non-linearity of the financial and economic systems by using the tools of statistical mechanics and information theory. More precisely, this thesis…

Statistical Finance · Quantitative Finance 2024-08-30 Rubina Zadourian

Predictive models of student success in Massive Open Online Courses (MOOCs) are a critical component of effective content personalization and adaptive interventions. In this article we review the state of the art in predictive models of…

Computers and Society · Computer Science 2018-04-23 Josh Gardner , Christopher Brooks

Context: Mobile devices have become an essential element in our daily lives, even for connecting to the Internet. Consequently, Web services have become extremely important when offering services through the Internet. However, current Web…

Software Engineering · Computer Science 2024-01-30 Guadalupe Ortiz , Alfonso Garcia-de-Prado

A key functionality of emerging connected autonomous systems such as smart transportation systems, smart cities, and the industrial Internet-of-Things, is the ability to process and learn from data collected at different physical locations.…

Machine Learning · Computer Science 2021-01-26 Konstantinos Gatsis

An approach for engineering student exercises using the Internet is described. In this approach, for a given exercise, each student receives the same problem, but with different data. The exercise content can be static or dynamic, and the…

Computers and Society · Computer Science 2012-08-26 Richard Perry

This note presents reflections drawn from my recent experiences in teaching a course on mathematics and sustainability, with a particular emphasis on raising awareness of the topic and its broader implications. The lectures were structured…

History and Overview · Mathematics 2025-10-16 Henrik Shahgholian

Different techniques, used to optimise on-line principal component analysis, are investigated by methods of statistical mechanics. These include local and global optimisation of node-dependent learning-rates which are shown to be very…

Disordered Systems and Neural Networks · Physics 2009-10-31 E Schloesser , D Saad , M Biehl

Decision theories offer principled methods for making choices under various types of uncertainty. Algorithms that implement these theories have been successfully applied to a wide range of real-world problems, including materials and drug…

Machine Learning · Computer Science 2026-05-26 Agustinus Kristiadi
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