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ENHANCING PRIVACY AND ACCURACY IN FEDERATED LEARNING FOR REGRESSION WITH SERVER-SIDE FILTERING TO ADDRESS OUTLIERS
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| Published in: | Computer Science (AGH University) |
|---|---|
| Format: | Online Article RSS Article |
| Published: |
2026
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| Subjects: | |
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| _version_ | 1868553612689408002 |
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| collection | WordPress RSS FRELIP Feed Integration |
| container_title | Computer Science (AGH University) |
| description | |
| discipline_display | Computer Sciience |
| discipline_facet | Computer Sciience |
| format | Online Article RSS Article |
| genre | Journal Article |
| id | rss_article:77642 |
| institution | FRELIP |
| journal_source_facet | Computer Science (AGH University) |
| last_indexed | 2026-06-20T21:39:49.249Z |
| publishDate | 2026 |
| publishDateSort | 2026 |
| record_format | rss_article |
| spellingShingle | ENHANCING PRIVACY AND ACCURACY IN FEDERATED LEARNING FOR REGRESSION WITH SERVER-SIDE FILTERING TO ADDRESS OUTLIERS Computer Sciience General Computer Sciience |
| sub_discipline_display | General |
| sub_discipline_facet | General |
| subject_display | Computer Sciience General Computer Sciience |
| subject_facet | Computer Sciience General Computer Sciience |
| title | ENHANCING PRIVACY AND ACCURACY IN FEDERATED LEARNING FOR REGRESSION WITH SERVER-SIDE FILTERING TO ADDRESS OUTLIERS |
| title_alt | MEJORANDO LA PRIVACIDAD Y PRECISIÓN EN APRENDIZAJE FEDERADO PARA REGRESIÓN CON FILTRADO DEL LADO DEL SERVIDOR PARA ABORDAR VALORES ATÍPICOS AMÉLIORATION DE LA CONFIDENTIALITÉ ET DE LA PRÉCISION DANS L'APPRENTISSAGE FÉDÉRÉ POUR LA RÉGRESSION AVEC FILTRAGE CÔTÉ SERVEUR POUR TRAITER LES VALEURS ABERRANTES MELHORANDO A PRIVACIDADE E A PRECISÃO NO APRENDIZADO FEDERADO PARA REGRESSÃO COM FILTRAGEM NO LADO DO SERVIDOR PARA LIDAR COM OUTLIERS |
| title_auth | ENHANCING PRIVACY AND ACCURACY IN FEDERATED LEARNING FOR REGRESSION WITH SERVER-SIDE FILTERING TO ADDRESS OUTLIERS |
| title_es_txt | MEJORANDO LA PRIVACIDAD Y PRECISIÓN EN APRENDIZAJE FEDERADO PARA REGRESIÓN CON FILTRADO DEL LADO DEL SERVIDOR PARA ABORDAR VALORES ATÍPICOS |
| title_fr_txt | AMÉLIORATION DE LA CONFIDENTIALITÉ ET DE LA PRÉCISION DANS L'APPRENTISSAGE FÉDÉRÉ POUR LA RÉGRESSION AVEC FILTRAGE CÔTÉ SERVEUR POUR TRAITER LES VALEURS ABERRANTES |
| title_full | ENHANCING PRIVACY AND ACCURACY IN FEDERATED LEARNING FOR REGRESSION WITH SERVER-SIDE FILTERING TO ADDRESS OUTLIERS |
| title_fullStr | ENHANCING PRIVACY AND ACCURACY IN FEDERATED LEARNING FOR REGRESSION WITH SERVER-SIDE FILTERING TO ADDRESS OUTLIERS |
| title_full_unstemmed | ENHANCING PRIVACY AND ACCURACY IN FEDERATED LEARNING FOR REGRESSION WITH SERVER-SIDE FILTERING TO ADDRESS OUTLIERS |
| title_pt_txt | MELHORANDO A PRIVACIDADE E A PRECISÃO NO APRENDIZADO FEDERADO PARA REGRESSÃO COM FILTRAGEM NO LADO DO SERVIDOR PARA LIDAR COM OUTLIERS |
| title_short | ENHANCING PRIVACY AND ACCURACY IN FEDERATED LEARNING FOR REGRESSION WITH SERVER-SIDE FILTERING TO ADDRESS OUTLIERS |
| title_sort | enhancing privacy and accuracy in federated learning for regression with server-side filtering to address outliers |
| topic | Computer Sciience General Computer Sciience |
| url | https://journals.agh.edu.pl/csci/article/view/7029 |