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In problem solving, understanding the problem that one seeks to solve is an essential initial step. In this paper, we propose computational methods for facilitating problem understanding through the task of recognizing the unknown in…

Computation and Language · Computer Science 2021-11-30 Ndapa Nakashole

Significant research has been carried out in the past half-century on defining generalised determinants for transformations between (typically real) vector spaces of different dimensions. We review three different generalisations of the…

General Mathematics · Mathematics 2019-04-18 Abhimanyu Pallavi Sudhir

Explainable artificial intelligence techniques are developed at breakneck speed, but suitable evaluation approaches lag behind. With explainers becoming increasingly complex and a lack of consensus on how to assess their utility, it is…

Human-Computer Interaction · Computer Science 2023-04-18 Edward Small , Yueqing Xuan , Danula Hettiachchi , Kacper Sokol

We introduce a new logic that combines Adjoint Logic with Graded Necessity Modalities. This results in a very expressive system capable of controlling when and how structural rules are used. We give a sequent calculus, natural deduction,…

Logic in Computer Science · Computer Science 2020-06-17 Harley Eades , Dominic Orchard

This text contains over three hundred specific open questions on various topics in additive combinatorics, each placed in context by reviewing all relevant results. While the primary purpose is to provide an ample supply of problems for…

Number Theory · Mathematics 2017-09-01 Bela Bajnok

Pausinger recently investigated a special determinant involving prime numbers. In this short note we point out that this type of determinants was already known in linear algebra and its computation is unrelated to prime numbers.

General Mathematics · Mathematics 2025-12-25 Huan Xiao

The question of obtaining well-defined criteria for multiple criteria decision making problems is well-known. One of the approaches dealing with this question is the concept of nonessential objective function. A certain objective function…

Optimization and Control · Mathematics 2008-11-08 Agnieszka B. Malinowska , Delfim F. M. Torres

Triple difference-in-differences designs are widely used to estimate causal effects in empirical work. Surveying the literature, we find that most applications include controls. We show that this standard practice is generally biased for…

Econometrics · Economics 2025-06-13 Dor Leventer

Evidential reasoning is cast as the problem of simplifying the evidence-hypothesis relation and constructing combination formulas that possess certain testable properties. Important classes of evidence as identifiers, annihilators, and…

Artificial Intelligence · Computer Science 2013-04-11 Yizong Cheng , Rangasami L. Kashyap

One of the most significant challenges in Computing Determinant of Rectangular Matrices is high time complexity of its algorithm. Among all definitions of determinant of rectangular matrices, used definition has special features which make…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-08-07 Neda Abdollahi , Mohammad Jafari , Morteza Bayat , Ali Amiri , Mahmood Fathy

Recently there has been several works estimating the number of $n\times n$ matrices with elements from some finite sets $\mathcal X$ of arithmetic interest and of a given determinant. Typically such results are compared with the trivial…

Number Theory · Mathematics 2024-08-09 Ilya D. Shkredov , Igor E. Shparlinski

Due to the increasing use of machine learning in practice it becomes more and more important to be able to explain the prediction and behavior of machine learning models. An instance of explanations are counterfactual explanations which…

Machine Learning · Computer Science 2019-11-19 André Artelt , Barbara Hammer

Expert systems applications that involve uncertain inference can be represented by a multidimensional contingency table. These tables offer a general approach to inferring with uncertain evidence, because they can embody any form of…

Artificial Intelligence · Computer Science 2013-04-15 David S. Vaughan , Bruce M. Perrin , Robert M. Yadrick , Peter D. Holden , Karl G. Kempf

Decision support tools enable improved decision-making for challenging decision problems by empowering stakeholders to process, analyze, visualize, and otherwise make sense of a variety of key factors. Their intentional design is a critical…

Computers and Society · Computer Science 2021-11-12 Narges Ahani , Andrew C. Trapp

We present a prototype of an integrated reasoning environment for educational purposes. The presented tool is a fragment of a proof assistant and automated theorem prover. We describe the existing and planned functionality of the theorem…

Human-Computer Interaction · Computer Science 2018-03-06 Mario Frank , Christoph Kreitz

The purpose of this article is to delve into the properties of invariants. The properties, explained in [2], reveal new ways to develop algorithms that allow us to test the primality of a number. In this article, some of these are shown,…

Number Theory · Mathematics 2023-08-02 Juan Hernandez-Toro

The features of a logically sound approach to a theory of statistical reasoning are discussed. A particular approach that satisfies these criteria is reviewed. This is seen to involve selection of a model, model checking, elicitation of a…

Statistics Theory · Mathematics 2018-05-09 Luai Al-Labadi , Zeynep Baskurt , Michael Evans

It seems that in the current age, computers, computation, and data have an increasingly important role to play in scientific research and discovery. This is reflected in part by the rise of machine learning and artificial intelligence,…

Machine Learning · Computer Science 2024-05-15 Ronan Keane

This thesis embarks on a comprehensive exploration of formal computational models that underlie typed programming languages. We focus on programming calculi, both functional (sequential) and concurrent, as they provide a compelling rigorous…

Logic in Computer Science · Computer Science 2024-08-16 Joseph William Neal Paulus

Spurred on by recent successes in causal inference competitions, Bayesian nonparametric (and high-dimensional) methods have recently seen increased attention in the causal inference literature. In this paper, we present a comprehensive…

Methodology · Statistics 2022-01-11 Antonio R. Linero , Joseph L. Antonelli
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