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http://hdl.handle.net/1942/36583
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DC Field | Value | Language |
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dc.contributor.author | NAPOLES RUIZ, Gonzalo | - |
dc.contributor.author | Grau, Isel | - |
dc.contributor.author | CONCEPCION PEREZ, Leonardo | - |
dc.contributor.author | KOUTSOVITI-KOUMERI, Lisa | - |
dc.contributor.author | Papa, João Paulo | - |
dc.date.accessioned | 2022-02-01T15:23:22Z | - |
dc.date.available | 2022-02-01T15:23:22Z | - |
dc.date.issued | 2022 | - |
dc.date.submitted | 2022-01-25T17:47:56Z | - |
dc.identifier.citation | NEUROCOMPUTING, | - |
dc.identifier.issn | 0925-2312 | - |
dc.identifier.uri | http://hdl.handle.net/1942/36583 | - |
dc.description.abstract | This paper presents a Fuzzy Cognitive Map model to quantify implicit bias in structured datasets where features can be numeric or discrete. In our proposal, problem features are mapped to neural concepts that are initially activated by experts when running what-if simulations, whereas weights connecting the neural concepts represent absolute correlation/association patterns between features. In addition, we introduce a new reasoning mechanism equipped with a normalization-like transfer function that prevents neurons from saturating. Another advantage of this new reasoning mechanism is that it can easily be controlled by regulating nonlinearity when updating neurons’ activation values in each iteration. Finally, we study the convergence of our model and derive analytical conditions concerning the existence and unicity of fixed-point attractors. | - |
dc.language.iso | en | - |
dc.publisher | - | |
dc.rights | 2022 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). | - |
dc.subject.other | fairness | - |
dc.subject.other | implicit bias | - |
dc.subject.other | fuzzy cognitive maps | - |
dc.subject.other | convergence analysis | - |
dc.title | Modeling Implicit Bias with Fuzzy Cognitive Maps | - |
dc.type | Journal Contribution | - |
dc.identifier.epage | 45 | - |
dc.identifier.spage | 33 | - |
dc.identifier.volume | 481 | - |
local.bibliographicCitation.jcat | A1 | - |
local.publisher.place | RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS | - |
local.type.refereed | Refereed | - |
local.type.specified | Article | - |
dc.identifier.doi | 10.1016/j.neucom.2022.01.070 | - |
dc.identifier.isi | 000761785300004 | - |
dc.identifier.eissn | 1872-8286 | - |
local.provider.type | CrossRef | - |
local.uhasselt.uhpub | yes | - |
local.uhasselt.international | yes | - |
item.contributor | NAPOLES RUIZ, Gonzalo | - |
item.contributor | Grau, Isel | - |
item.contributor | CONCEPCION PEREZ, Leonardo | - |
item.contributor | KOUTSOVITI-KOUMERI, Lisa | - |
item.contributor | Papa, João Paulo | - |
item.fulltext | With Fulltext | - |
item.validation | ecoom 2023 | - |
item.fullcitation | NAPOLES RUIZ, Gonzalo; Grau, Isel; CONCEPCION PEREZ, Leonardo; KOUTSOVITI-KOUMERI, Lisa & Papa, João Paulo (2022) Modeling Implicit Bias with Fuzzy Cognitive Maps. In: NEUROCOMPUTING,. | - |
item.accessRights | Open Access | - |
crisitem.journal.issn | 0925-2312 | - |
crisitem.journal.eissn | 1872-8286 | - |
Appears in Collections: | Research publications |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
1-s2.0-S092523122200090X-main.pdf | Published version | 1.25 MB | Adobe PDF | View/Open |
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