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Deep learning has emerged as a strong and efficient framework that can be applied to a broad spectrum of complex learning problems which were difficult to solve using the traditional machine learning techniques in the past. In the last few…

Machine Learning · Computer Science 2018-10-02 Anirban Chakraborty , Manaar Alam , Vishal Dey , Anupam Chattopadhyay , Debdeep Mukhopadhyay

Can the cross product be generalized? Why are the trace and determinant so important in matrix theory? What do all the coefficients of the characteristic polynomial represent? This paper describes a technique for `doodling' equations from…

History and Overview · Mathematics 2007-12-14 Elisha Peterson

Convenient parameterizations of matrices in terms of vectors transform (certain classes of) matrix equations into covariant (hence rotation-invariant) vector equations. Certain recently introduced such parameterizations are tersely…

Exactly Solvable and Integrable Systems · Physics 2009-11-10 M. Bruschi , F. Calogero

A major reason behind the success of probability calculus is that it possesses a number of valuable tools, which are based on the notion of probabilistic independence. In this paper, I identify a notion of logical independence that makes…

Artificial Intelligence · Computer Science 2013-03-08 Adnan Darwiche

There are various interesting semantics' (extensions) designed for argumentation frameworks. They enable to assign a meaning, e.g., to odd-length cycles. Our main motivation is to transfer semantics' proposed by Baroni, Giacomin and Guida…

Logic in Computer Science · Computer Science 2011-08-29 Monika Adamova , Jan Sefranek

Current methods for textual analysis rely on data annotated within predefined ontologies, often embedding human bias within black-box models. Despite achieving near-perfect performance, these approaches exploit unstructured, linear pattern…

Computation and Language · Computer Science 2026-03-11 Diego Revilla , Martin Fernandez-de-Retana , Lingfeng Chen , Aritz Bilbao-Jayo , Miguel Fernandez-de-Retana

Preference-based argumentation frameworks (PAFs) extend Dung's approach to abstract argumentation (AAFs) by encoding preferences over arguments. Such preferences control the transformation of attacks into defeats, and different approaches…

Artificial Intelligence · Computer Science 2026-04-28 Alessio Zaninotto , Bruno Yun , Nir Oren , Srdjan Vesic

In this article, we present a novel approach for parsing argumentation structures. We identify argument components using sequence labeling at the token level and apply a new joint model for detecting argumentation structures. The proposed…

Computation and Language · Computer Science 2016-07-25 Christian Stab , Iryna Gurevych

Existing multi-expert LLM systems gather diverse perspectives but combine them through simple aggregation, obscuring which arguments drove the final decision. We introduce ARGORA, a framework that organizes multi-expert discussions into…

Artificial Intelligence · Computer Science 2026-01-30 Youngjin Jin , Hanna Kim , Kwanwoo Kim , Chanhee Lee , Seungwon Shin

We present in this paper some fundamental tools for developing matrix analysis over the complex quaternion algebra. As applications, we consider generalized inverses, eigenvalues and eigenvectors, similarity, determinants of complex…

Rings and Algebras · Mathematics 2007-05-23 Yongge Tian

In Dung-style abstract argumentation, various semantics capture notions of acceptability of arguments. The admissibility semantics capture the notion that an argument can be consistently defended from any potential counterargument. Weak…

Artificial Intelligence · Computer Science 2026-05-05 Uri Andrews , Luca San Mauro , John Spoerl

Recently, decision trees (DT) have been used as an explainable representation of controllers (a.k.a. strategies, policies, schedulers). Although they are often very efficient and produce small and understandable controllers for discrete…

Machine Learning · Computer Science 2022-08-30 Florian Jüngermann , Jan Křetínský , Maximilian Weininger

Despite the recent, widespread focus on eXplainable AI (XAI), explanations computed by XAI methods tend to provide little insight into the functioning of Neural Networks (NNs). We propose a novel framework for obtaining (local) explanations…

Artificial Intelligence · Computer Science 2021-06-15 Emanuele Albini , Piyawat Lertvittayakumjorn , Antonio Rago , Francesca Toni

Recently, sub-indices and sub-factors of groups with connections to number theory, additive combinatorics, and factorization of groups have been introduced and studied. Since all group subsets are considered in the theory and there are many…

Group Theory · Mathematics 2023-10-06 M. H. Hooshmand , M. M. Yousefian Arani

Explainable artificial intelligence (XAI) methods are portrayed as a remedy for debugging and trusting statistical and deep learning models, as well as interpreting their predictions. However, recent advances in adversarial machine learning…

Cryptography and Security · Computer Science 2025-07-30 Hubert Baniecki , Przemyslaw Biecek

Humans engage in informal debates on a daily basis. By expressing their opinions and ideas in an argumentative fashion, they are able to gain a deeper understanding of a given problem and in some cases, find the best possible course of…

Logic in Computer Science · Computer Science 2019-12-13 Ria Jha , Francesco Belardinelli , Francesca Toni

As algorithmic decision-making systems become more prevalent in society, ensuring the fairness of these systems is becoming increasingly important. Whilst there has been substantial research in building fair algorithmic decision-making…

Machine Learning · Computer Science 2023-10-30 Madeleine Waller , Odinaldo Rodrigues , Oana Cocarascu

In this paper we discuss contrastive explanations for formal argumentation - the question why a certain argument (the fact) can be accepted, whilst another argument (the foil) cannot be accepted under various extension-based semantics. The…

Artificial Intelligence · Computer Science 2022-01-26 AnneMarie Borg , Floris Bex

The fundamental elements of evidential reasoning problems are described, followed by a discussion of the structure of various types of problems. Bayesian inference networks and state space formalism are used as the tool for problem…

Artificial Intelligence · Computer Science 2013-04-12 Moshe Ben-Bassat

We are interested in the numerical solution of nonsymmetric linear systems arising from the discretization of convection-diffusion partial differential equations with separable coefficients and dominant convection. Preconditioners based on…

Numerical Analysis · Mathematics 2015-01-14 Davide Palitta , Valeria Simoncini
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