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Strategic classification regards the problem of learning in settings where users can strategically modify their features to improve outcomes. This setting applies broadly and has received much recent attention. But despite its practical…

Machine Learning · Computer Science 2021-06-15 Sagi Levanon , Nir Rosenfeld

The utilization of statistical methods an their applications within the new field of study known as Topological Data Analysis has has tremendous potential for broadening our exploration and understanding of complex, high-dimensional data…

Applications · Statistics 2016-07-19 Patrick S. Medina , R. W. Doerge

Learning structural information from observational data is central to producing new knowledge outside the training corpus. This holds for mechanistic understanding in scientific discovery as well as flexible test-time compositional…

Computation and Language · Computer Science 2026-01-27 Michelle Chao Chen , Moritz Miller , Bernhard Schölkopf , Siyuan Guo

Recent approaches to human concept learning have successfully combined the power of symbolic, infinitely productive rule systems and statistical learning to explain our ability to learn new concepts from just a few examples. The aim of most…

Artificial Intelligence · Computer Science 2020-04-29 Pablo Tano , Sergio Romano , Mariano Sigman , Alejo Salles , Santiago Figueira

The use of simulation-based methods for introducing inference is growing in popularity for the Stat 101 course, due in part to increasing evidence of the methods ability to improve students' statistical thinking. This impact comes from…

Other Statistics · Statistics 2015-08-04 Nathan Tintle , Beth Chance , George Cobb , Soma Roy , Todd Swanson , Jill VanderStoep

This paper lays out the current landscape of tools used in statistics education. In particular, it considers graphing calculators, spreadsheets, applets and microworlds, standalone educational software, statistical programming tools, tools…

Computation · Statistics 2016-10-05 Amelia McNamara

Learning-based and data-driven techniques have recently become a subject of primary interest in the field of reconstruction and regularization of inverse problems. Besides the development of novel methods, yielding excellent results in…

Machine Learning · Statistics 2023-12-22 Luca Ratti

Science communication skills are considered essential learning objectives for undergraduate physics students. However, high enrollment and limited class resources present significant barriers to providing students ample opportunities to…

Physics Education · Physics 2024-09-17 Steven W. Tarr , Emily Alicea-Muñoz

Computational thinking is a key skill for space science graduates, who must apply advanced problem-solving skills to model complex systems, analyse big data sets, and develop control software for mission-critical space systems. We describe…

Usually the first course in mathematics is calculus. Its a core course in the curriculum of the Business, Engineering and the Sciences. However many students face difficulties to learn calculus. These difficulties are often caused by the…

Computers and Society · Computer Science 2012-12-27 Seifedine Kadry , Maha ElShalkamy

Epidemiologists have a growing interest in employing computational approaches to solve analytic problems, with simulation being arguably the most accessible among all approaches. While previous literature discussed the utility of simulation…

Computation · Statistics 2023-06-22 Boyi Guo , Linzi Li , Jacqueline E. Rudolph

An introductory formal languages course exposes advanced undergraduate and early graduate students to automata theory, grammars, constructive proofs, computability, and decidability. Programming students find these topics to be challenging…

Formal Languages and Automata Theory · Computer Science 2014-12-17 Marco T. Morazán , Rosario Antunez

This chapter opens with a review of classic tools for regression, a subset of machine learning that seeks to find relationships between variables. With the advent of scientific machine learning this field has moved from a purely data-driven…

Machine Learning · Statistics 2025-12-02 Miguel A. Mendez

As belief around the potential of computational social science grows, fuelled by recent advances in machine learning, data scientists are ostensibly becoming the new experts in education. Scholars engaged in critical studies of education…

Computers and Society · Computer Science 2025-09-04 Rebecca Eynon , Nabeel Gillani

Probabilistic programming is becoming increasingly popular thanks to its ability to specify problems with a certain degree of uncertainty. In this work, we focus on term rewriting, a well-known computational formalism. In particular, we…

Programming Languages · Computer Science 2025-03-20 Germán Vidal

In the 1990s, statisticians began thinking in a principled way about how computation could better support the learning and doing of statistics. Since then, the pace of software development has accelerated, advancements in computing and data…

Computation · Statistics 2018-06-05 Amelia McNamara

Data visualization is a core part of statistical practice and is ubiquitous in many fields. Although there are numerous books on data visualization, instructors in statistics and data science may be unsure how to teach data visualization,…

Other Statistics · Statistics 2025-07-31 Zach Branson , Monica Paz Parra , Ronald Yurko

Language is a social phenomenon and variation is inherent to its social nature. Recently, there has been a surge of interest within the computational linguistics (CL) community in the social dimension of language. In this article we present…

Computation and Language · Computer Science 2016-04-07 Dong Nguyen , A. Seza Doğruöz , Carolyn P. Rosé , Franciska de Jong

The sequent calculus is a formalism for proving validity of statements formulated in First-Order Logic. It is routinely used in computer science modules on mathematical logic. Formal proofs in the sequent calculus are finite trees obtained…

Logic in Computer Science · Computer Science 2018-03-06 Arno Ehle , Norbert Hundeshagen , Martin Lange

Quantitative methods and mathematical modeling are playing an increasingly important role across disciplines. As a result, interdisciplinary mathematics courses are increasing in popularity. However, teaching such courses at an advanced…

Other Quantitative Biology · Quantitative Biology 2021-09-10 Mark Jayson Cortez , Alan Eric Akil , Krešimir Josić , Alexander J. Stewart