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Matrix seriation, the problem of permuting the rows and columns of a matrix to uncover latent structure, is a fundamental technique in data science, particularly in the visualization and analysis of relational data. Applications span…

Optimization and Control · Mathematics 2025-06-25 Víctor Blanco , Alfredo Marín , Justo Puerto

With the advancement of GPS and remote sensing technologies, large amounts of geospatial and spatiotemporal data are being collected from various domains, driving the need for effective and efficient prediction methods. Given spatial data…

Machine Learning · Computer Science 2020-12-25 Zhe Jiang

Spreadsheet tables are often labeled, and these labels effectively constitute types for the data in the table. In such cases tables can be considered to be built from typed data where the placement of values within the table is controlled…

Software Engineering · Computer Science 2018-09-11 Martin Erwig

Commercially available scheduling tools such as Primavera and Microsoft Project fail to provide information pertaining to the spatial aspects of construction project. A methodology using geographical information systems (GIS) is developed…

Other Computer Science · Computer Science 2008-03-26 V. K. Bansal , Mahesh Pal

We survey results in algebraic complexity theory, focusing on matrix multiplication. Our goals are (i.) to show how open questions in algebraic complexity theory are naturally posed as questions in geometry and representation theory, (ii.)…

Computational Complexity · Computer Science 2007-05-23 J. M. Landsberg

This paper offers a brief review of cognitive verbs typically used in the literature to describe standard spreadsheet practices. The verbs identified are then categorised in terms of Bloom's Taxonomy of Hierarchical Levels, and then rated…

Human-Computer Interaction · Computer Science 2008-07-21 Garry Cleere

Solving Sudoku puzzles is one of the most popular pastimes in the world. Puzzles range in difficulty from easy to very challenging; the hardest puzzles tend to have the most empty cells. The current paper explains and compares three…

Optimization and Control · Mathematics 2013-05-17 Eric C. Chi , Kenneth Lange

Simulation has become the evaluation method of choice for many areas of distributing computing research. However, most existing simulation packages have several limitations on the size and complexity of the system being modeled. Fine…

Distributed, Parallel, and Cluster Computing · Computer Science 2011-07-01 Dobre Ciprian , Cristea Valentin , Iosif C. Legrand

We propose a presentation of classical propositional tableaux elaborated by application of methods that are noteworthy in program design, namely program derivation with separation of concerns. We start by deriving from a straightforward…

Computers and Society · Computer Science 2015-07-15 Juan Michelini , Alvaro Tasistro

Current prescriptions for spreadsheet style specify modular separation of data, calcu1ation and output, based on the notion that writing a spreadsheet is like writing a computer program. Instead of a computer programming style, this article…

Human-Computer Interaction · Computer Science 2008-07-22 John F. Raffensperger

Tables are among the most powerful and practical tools for organizing and working with data. Our motivation is to equip spreadsheet programs with smart assistance capabilities. We concentrate on one particular family of tables, namely,…

Information Retrieval · Computer Science 2017-08-30 Shuo Zhang , Krisztian Balog

Experts in different domains rely increasingly on simulation models of complex processes to reach insights, make decisions, and plan future projects. These models are often used to study possible trade-offs, as experts try to optimise…

Human-Computer Interaction · Computer Science 2019-02-06 Nadia Boukhelifa , Anastasia Bezerianos , Ioan Cristian Trelea , Nathalie Mejean Perrot , Evelyne Lutton

Supervised dimensionality reduction has emerged as an important theme in the last decade. Despite the plethora of models and formulations, there is a lack of a simple model which aims to project the set of patterns into a space defined by…

Machine Learning · Statistics 2016-10-28 Anthony O. Smith , Anand Rangarajan

This paper presents an analytical taxonomy that can suitably describe, rather than simply classify, techniques for data presentation. Unlike previous works, we do not consider particular aspects of visualization techniques, but their…

Learning implicit representations has been a widely used solution for surface reconstruction from 3D point clouds. The latest methods infer a distance or occupancy field by overfitting a neural network on a single point cloud. However,…

Computer Vision and Pattern Recognition · Computer Science 2023-08-28 Chao Chen , Yu-Shen Liu , Zhizhong Han

The recent advancements in machine learning have motivated researchers to generate classification models dealing with hundreds of classes such as in the case of image datasets. However, visualization of classification models with high…

Human-Computer Interaction · Computer Science 2023-09-13 Nina Mir , Ragaad AlTarawneh , Shah Rukh Humayoun

A data structure and toolkit are presented here that allow for the description and manipulation of mathematical models of three-manifolds and their interactive display from multiple viewpoints via the OpenGL 3D graphics package. The data…

Computational Geometry · Computer Science 2012-01-30 Don V. Black

Research on formulae production in spreadsheets has established the practice as high risk yet unrecognised as such by industry. There are numerous software applications that are designed to audit formulae and find errors. However these are…

Human-Computer Interaction · Computer Science 2008-03-13 Simon Thorne , David Ball , Zoe Lawson

This paper demonstrates a methodology to help practitioners maximise the utility of complex multidisciplinary engineering models implemented as spreadsheets, an area presenting unique challenges. As motivation we investigate the expanding…

Software Engineering · Computer Science 2014-01-21 David Birch , Helen Liang , Paul H J Kelly , Glen Mullineux , Tony Field , Joan Ko , Alvise Simondetti

Riemannian diffusion models draw inspiration from standard Euclidean space diffusion models to learn distributions on general manifolds. Unfortunately, the additional geometric complexity renders the diffusion transition term inexpressible…

Machine Learning · Computer Science 2023-11-01 Aaron Lou , Minkai Xu , Stefano Ermon
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