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Interestingness measures provide information that can be used to prune or select association rules. A given value of an interestingness measure is often interpreted relative to the overall range of the values that the interestingness…

Applications · Statistics 2013-08-20 Mateen Shaikh , Paul D. McNicholas , M. Luiza Antonie , T. Brendan Murphy

Every one knows that an equation is equivalent to a multivariate function. Generally speaking, there are more than one unknown x in this multivariate function and it is not easy to reduce the number of unknown x to one. In this paper we…

General Mathematics · Mathematics 2018-10-09 Zi Qian Wu

A qualitatively new, much more liberal and efficient organisation of science is proposed and justified, in connection with growing debate about further role and development of fundamental science. Although the key ideas can be explained…

General Physics · Physics 2007-05-23 Andrei P. Kirilyuk

We present functions that quantify the contribution of a set of arguments in quantitative bipolar argumentation graphs to (the final strength of) an argument of interest, a so-called topic. Our set contribution functions are generalizations…

Artificial Intelligence · Computer Science 2026-04-03 Filip Naudot , Andreas Brännström , Vicenç Torra , Timotheus Kampik

Compositional generalization is the capacity to recognize and imagine a large amount of novel combinations from known components. It is a key in human intelligence, but current neural networks generally lack such ability. This report…

Artificial Intelligence · Computer Science 2021-02-09 Yuanpeng Li

In this paper we investigate the complexity of abduction, a fundamental and important form of non-monotonic reasoning. Given a knowledge base explaining the world's behavior it aims at finding an explanation for some observed manifestation.…

Computational Complexity · Computer Science 2010-06-28 Nadia Creignou , Johannes Schmidt , Michael Thomas

Choice functions constitute a simple, direct and very general mathematical framework for modelling choice under uncertainty. In particular, they are able to represent the set-valued choices that appear in imprecise-probabilistic decision…

Artificial Intelligence · Computer Science 2019-05-22 Jasper De Bock , Gert de Cooman

A new class of functions is presented. The structure of the algorithm, particularly the selection criteria (branching), is used to define the fundamental property of the new class. The most interesting property of the new functions is that…

Computational Complexity · Computer Science 2020-02-25 Rade Vuckovac

Interpretability is the study of explaining models in understandable terms to humans. At present, interpretability is divided into two paradigms: the intrinsic paradigm, which believes that only models designed to be explained can be…

Machine Learning · Computer Science 2024-11-14 Andreas Madsen , Himabindu Lakkaraju , Siva Reddy , Sarath Chandar

Recently, the partial information decomposition emerged as a promising framework for identifying the meaningful components of the information contained in a joint distribution. Its adoption and practical application, however, have been…

Information Theory · Computer Science 2018-08-28 Ryan G. James , Jeffrey Emenheiser , James P. Crutchfield

Pairwise comparisons between alternatives are a well-established tool to decompose decision problems into smaller and more easily tractable sub-problems. However, due to our limited rationality, the subjective preferences expressed by…

Artificial Intelligence · Computer Science 2016-03-15 Matteo Brunelli

Compositionality has traditionally been understood as a major factor in productivity of language and, more broadly, human cognition. Yet, recently, some research started to question its status, showing that artificial neural networks are…

Computation and Language · Computer Science 2022-06-13 Michal Auersperger , Pavel Pecina

Compositionality is a key property for dealing with complexity, which has been studied from many points of view in diverse fields. Particularly, the composition of individual computations (or programs) has been widely studied almost since…

Logic in Computer Science · Computer Science 2022-06-06 Damian Arellanes

For systems consisting of distinguishable particles, there exists an agreed upon notion of entanglement which is fundamentally based on the possibility of addressing individually each one of the constituent parties. Instead, the…

Quantum Physics · Physics 2020-09-24 F. Benatti , R. Floreanini , F. Franchini , U. Marzolino

Modifiable combining functions are a synthesis of two common approaches to combining evidence. They offer many of the advantages of these approaches and avoid some disadvantages. Because they facilitate the acquisition, representation,…

Artificial Intelligence · Computer Science 2013-04-11 Paul Cohen , Glenn Shafer , Prakash P. Shenoy

When we work with information from multiple sources, the formalism each employs to handle uncertainty may not be uniform. In order to be able to combine these knowledge bases of different formats, we need to first establish a common basis…

Artificial Intelligence · Computer Science 2013-02-18 Choh Man Teng

A hallmark of human intelligence is the ability to construct self-contained chunks of knowledge and adequately reuse them in novel combinations for solving different yet structurally related problems. Learning such compositional structures…

Machine Learning · Computer Science 2021-03-18 Jorge A. Mendez , Eric Eaton

For any polynomial f with complex coefficients we find a remarkable subset of poles of the motivic zeta function. It is combinatorially determined by any log resolution and it admits an intrinsic interpretation in terms of contact loci of…

Algebraic Geometry · Mathematics 2026-02-17 Nero Budur , Eduardo de Lorenzo Poza , Quan Shi , Huaiqing Zuo

Political polarization is perceived as a threat to democracies. Using the Galam model of opinion dynamics deployed in a five-dimensional parameter space, I show that polarization is the byproduct of an essential hallmark of a vibrant…

Physics and Society · Physics 2023-07-19 Serge Galam

Unexpectedness is a central concept in Simplicity Theory, a theory of cognition relating various inferential processes to the computation of Kolmogorov complexities, rather than probabilities. Its predictive power has been confirmed by…

Artificial Intelligence · Computer Science 2023-11-16 Giovanni Sileno , Jean-Louis Dessalles