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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Page: 1 2 3 Hits 1 – 20 of 48 1 Enhancing Attention’s Explanation Using Interpretable Tsetlin Machine Rohan Kumar Yadav; Dragoş Constantin Nicolae In: Algorithms; Volume 15; Issue 5; Pages: 143 (2022) BASE Show details 2 Training dynamics of neural language models ... Saphra, Naomi. - : The University of Edinburgh, 2021 BASE Show details 3 Explainable Multimodal Fusion Alvi, Jaweriah. - : KTH, Skolan för elektroteknik och datavetenskap (EECS), 2021 BASE Show details 4 Training dynamics of neural language models Saphra, Naomi. - : The University of Edinburgh, 2021 BASE Show details 5 Multilingual BERT, Ergativity, and Grammatical Subjecthood Papadimitriou, Isabel; Chi, Ethan A.; Futrell, Richard... In: Proceedings of the Society for Computation in Linguistics (2021) BASE Show details 6 Interpreting agreement: Evidence from Japanese object honorifics Ikawa, Shiori In: Proceedings of the Linguistic Society of America; Vol 6, No 1 (2021): Proceedings of the Linguistic Society of America; 228–242 ; 2473-8689 (2021) BASE Show details 7 Relational concept analysis: a polyvalent tool for knowledge extraction ; Analyse relationnelle de concepts : une méthode polyvalente pour l'extraction de connaissance Wajnberg, Mickael. - : HAL CCSD, 2020 In: https://hal.archives-ouvertes.fr/tel-03042085 ; Informatique [cs]. Université du Québec à Montréal; Université de Lorraine, 2020. Français. ⟨NNT : 2020LORR0136⟩ (2020) BASE Show details 8 Investigating the learnability of uninterpretable features in advanced L2 Greek grammars ... Δαναβάση, Τερψιθέα Γ.. - : Aristotle University of Thessaloniki, 2020 BASE Show details 9 Designing Fair AI for Managing Employees in Organizations: A Review, Critique, and Design Agenda Robert, Lionel + "Jr"; Pierce, Casey; Morris, Liz. - : Human-Computer Interaction, 2020 BASE Show details 10 Interpretability for Deep Learning Text Classifiers Lucaci, Diana. - : Université d'Ottawa / University of Ottawa, 2020 BASE Show details 11 Learning discrete word embeddings to achieve better interpretability and processing efficiency Beland-Leblanc, Samuel. - 2020 BASE Show details 12 Interpreting Sequence-to-Sequence Models for Russian Inflectional Morphology King, David L; Sims, Andrea D; Elsner, Micha In: Proceedings of the Society for Computation in Linguistics (2020) BASE Show details 13 Acquisition of English Auxiliary Stranding Constructions by Persian EFL Learners Fatemeh Khezri; Mohammad Javad Rezai; Mohammad Hasan Razmi... In: Applied Linguistics Research Journal, Vol 4, Iss 2, Pp 54-67 (2020) (2020) BASE Show details 14 Η κατάκτηση του γένους στη Νέα Ελληνική ως δεύτερη γλώσσα ... Τσιούσια, Κωνσταντίνα Απόστολου. - : Aristotle University of Thessaloniki, 2019 BASE Show details 15 L2 acquisition of interrogative and relative clauses by Greek learners of English: that-trace effects and subject-object extraction ... Filiou, Dimitra. - : Selected papers on theoretical and applied linguistics, 2019 BASE Show details 16 Non-Entailed Subsequences as a Challenge for Natural Language Inference McCoy, Richard T.; Linzen, Tal In: Proceedings of the Society for Computation in Linguistics (2019) BASE Show details 17 INTERPRETABILITY OF FUZZY TEMPORAL MODELS ... Dolgy, A.I.; Kovalev, S.M.. - : Southern Federal University, 2018 BASE Show details 18 Rnn Models For Representation Of Linguistic Form And Function In Recurrent Neural Networks ... Kádár, Ákos; Chrupała, Grzegorz; Alishahi, Afra. - : Zenodo, 2017 BASE Show details 19 Rnn Models For Representation Of Linguistic Form And Function In Recurrent Neural Networks ... Kádár, Ákos; Chrupała, Grzegorz; Alishahi, Afra. - : Zenodo, 2017 BASE Show details 20 Why Linguistic Fuzzy Rule Based Classification Systems perform well in Big Data Applications? Fernández Hilario, Alberto; Altalhi, Abdulrahman; Alshomrani, Saleh; Herrera Triguero, Francisco. - : Atlantis Press, 2017 Abstract: The significance of addressing Big Data applications is beyond all doubt. The current ability of extracting interesting knowledge from large volumes of information provides great advantages to both corporations and academia. Therefore, researchers and practitioners must deal with the problem of scalability so that Machine Learning and Data Mining algorithms can address Big Data properly. With this end, the MapReduce programming framework is by far the most widely used mechanism to implement fault-tolerant distributed applications. This novel framework implies the design of a divide-and-conquer mechanism in which local models are learned separately in one stage (Map tasks) whereas a second stage (Reduce) is devoted to aggregate all sub-models into a single solution. In this paper, we focus on the analysis of the behavior of Linguistic Fuzzy Rule Based Classification Systems when embedded into a MapReduce working procedure. By retrieving different information regarding the rules learned throughout the MapReduce process, we will be able to identify some of the capabilities of this particular paradigm that allowed them to provide a good performance when addressing Big Data problems. In summary, we will show that linguistic fuzzy classifiers are a robust approach in case of scalability requirements. ; This work have been partially supported by the Spanish Ministry of Science and Technology under projects TIN2014-57251-P and TIN2015-68454-R. Keyword: Big data; Fuzzy rule based classification systems; Hadoop; Interpretability; MapReduce URL: http://hdl.handle.net/10481/49779 https://doi.org/10.2991/ijcis.10.1.80 BASE Hide details Page: 1 2 3

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