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Information fusion deals with the integration and merging of data and information from multiple (heterogeneous) sources. In many cases, the information that needs to be fused has security classification. The result of the fusion process is…

Cryptography and Security · Computer Science 2017-06-20 Magnus Jändel , Pontus Svenson , Ronnie Johansson

In Information fusion, the conflict is an important concept. Indeed, combining several imperfect experts or sources allows conflict. In the theory of belief functions, this notion has been discussed a lot. The mass appearing on the empty…

Artificial Intelligence · Computer Science 2017-09-14 Arnaud Martin

Selective rationalization has become a common mechanism to ensure that predictive models reveal how they use any available features. The selection may be soft or hard, and identifies a subset of input features relevant for prediction. The…

Computation and Language · Computer Science 2019-12-17 Mo Yu , Shiyu Chang , Yang Zhang , Tommi S. Jaakkola

Belief merging is an important but difficult problem in Artificial Intelligence, especially when sources of information are pervaded with uncertainty. Many merging operators have been proposed to deal with this problem in possibilistic…

Artificial Intelligence · Computer Science 2012-03-19 Guilin Qi , Jianfeng Du , Weiru Liu , David A. Bell

Reuse of data in new contexts beyond the purposes for which it was originally collected has contributed to technological innovation and reducing the consent burden on data subjects. One of the legal mechanisms that makes such reuse possible…

Computers and Society · Computer Science 2023-09-06 Asia J. Biega

In rule-based systems, goal-oriented computations correspond naturally to the possible ways that an observation may be explained. In some applications, we need to compute explanations for a series of observations with the same domain. The…

Artificial Intelligence · Computer Science 2007-05-23 Fangzhen Lin , Jia-Huai You

Linear fusion of estimates under the condition of no knowledge of correlation of estimation errors has reached maturity. On the other hand, various cases of partial knowledge are still active research areas. A frequent motivation is to deal…

Signal Processing · Electrical Eng. & Systems 2025-06-16 Jiří Ajgl , Ondřej Straka

In this contribution we explore choice revision, a sort of belief change in which the new information is represented by a set of sentences and the agent could accept some of the sentences while rejecting the others. We propose a generalized…

Logic in Computer Science · Computer Science 2018-05-04 Li Zhang

Seismic inversion and imaging are adjoint-based optimization problems that process up to terabytes of data, regularly exceeding the memory capacity of available computers. Data compression is an effective strategy to reduce this memory…

Computational Engineering, Finance, and Science · Computer Science 2021-09-21 Navjot Kukreja , Jan Hueckelheim , Mathias Louboutin , Fabio Luporini , Paul Hovland , Gerard Gorman

In this chapter, we present two applications in information fusion in order to evaluate the generalized proportional conflict redistribution rule presented in the chapter \cite{Martin06a}. Most of the time the combination rules are…

Computer Vision and Pattern Recognition · Computer Science 2008-12-18 Arnaud Martin , Christophe Osswald

Possibilistic logic offers a qualitative framework for representing pieces of information associated with levels of uncertainty of priority. The fusion of multiple sources information is discussed in this setting. Different classes of…

Artificial Intelligence · Computer Science 2013-01-18 Salem Benferhat , Didier Dubois , Souhila Kaci , Henri Prade

Choice revision is a sort of non-prioritized multiple revision, in which the agent partially accepts the new information represented by a set of sentences. We investigate the construction of choice revision based on a new approach to belief…

Logic · Mathematics 2018-05-02 Li Zhang

There are several contexts of non-monotonic reasoning where a priority between rules is established whose purpose is preventing conflicts. One formalism that has been widely employed for non-monotonic reasoning is the sceptical one known as…

Artificial Intelligence · Computer Science 2012-11-26 Guido Governatori , Francesco Olivieri , Simone Scannapieco , Matteo Cristani

A general method is given for revising degrees of belief and arriving at consistent decisions about a system of logically constrained issues. In contrast to other works about belief revision, here the constraints are assumed to be fixed.…

Artificial Intelligence · Computer Science 2012-03-09 Rosa Camps , Xavier Mora , Laia Saumell

Fine-tuning pre-trained language models, particularly large language models, demands extensive computing resources and can result in varying performance outcomes across different domains and datasets. This paper examines the approach of…

Computation and Language · Computer Science 2024-06-19 Guodong Du , Jing Li , Hanting Liu , Runhua Jiang , Shuyang Yu , Yifei Guo , Sim Kuan Goh , Ho-Kin Tang

Belief integration methods are often aimed at deriving a single and consistent knowledge base that retains as much as possible of the knowledge bases to integrate. The rationale behind this approach is the minimal change principle: the…

Artificial Intelligence · Computer Science 2007-05-23 Paolo Liberatore

Although many investigators affirm a desire to build reasoning systems that behave consistently with the axiomatic basis defined by probability theory and utility theory, limited resources for engineering and computation can make a complete…

Artificial Intelligence · Computer Science 2013-04-11 Eric J. Horvitz

Belief revision is an operation that aims at modifying old be-liefs so that they become consistent with new ones. The issue of belief revision has been studied in various formalisms, in particular, in qualitative algebras (QAs) in which the…

Artificial Intelligence · Computer Science 2014-12-15 Valmi Dufour-Lussier , Alice Hermann , Florence Le Ber , Jean Lieber

Artificial intelligence applications such as industrial robotics, military surveillance, and hazardous environment clean-up, require situation understanding based on partial, uncertain, and ambiguous or erroneous evidence. It is necessary…

Artificial Intelligence · Computer Science 2013-04-15 Tod S. Levitt

Spatial conjunction is a powerful construct for reasoning about dynamically allocated data structures, as well as concurrent, distributed and mobile computation. While researchers have identified many uses of spatial conjunction, its…

Logic in Computer Science · Computer Science 2007-05-23 Viktor Kuncak , Martin Rinard
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