Wisdom of the machines : federated learning using OPAL
Thesis: S.M., Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2018.
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| Format: | Thesis |
| Language: | eng |
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Massachusetts Institute of Technology
2019
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| Online Access: | http://hdl.handle.net/1721.1/120686 |
| _version_ | 1811076803374088192 |
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| author | Alotaibi, Abdulrahman |
| author2 | Alex 'Sandy' Pentland. |
| author_facet | Alex 'Sandy' Pentland. Alotaibi, Abdulrahman |
| author_sort | Alotaibi, Abdulrahman |
| collection | MIT |
| description | Thesis: S.M., Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2018. |
| first_indexed | 2024-09-23T10:27:50Z |
| format | Thesis |
| id | mit-1721.1/120686 |
| institution | Massachusetts Institute of Technology |
| language | eng |
| last_indexed | 2024-09-23T10:27:50Z |
| publishDate | 2019 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/1206862019-04-12T07:45:33Z Wisdom of the machines : federated learning using OPAL Federated learning using OPAL Alotaibi, Abdulrahman Alex 'Sandy' Pentland. Program in Media Arts and Sciences (Massachusetts Institute of Technology) Program in Media Arts and Sciences (Massachusetts Institute of Technology) Program in Media Arts and Sciences () Thesis: S.M., Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2018. Cataloged from PDF version of thesis. Includes bibliographical references (pages 67-68). Wisdom of the crowds (WOC) is an old concept that started by recording and aggregating people's estimations. It is one of the useful tools that exists today and allows many estimation applications to work correctly. Moreover, Open algorithms (OPAL) is a useful platform that enables institutions and individuals to share sensitive data, and increases the privacy of the data. In addition, federated learning is a new way to build and generate machine learning models by aggregating their hyperparameters. In this thesis, I show how to combine the three different concepts to build machine learning models on top of OPAL that utilize federated learning on a network. I then extend OPAL to support this new feature and demonstrate how to build a machine learning model using small independent models. by Abdulrahman Alotaibi. S.M. 2019-03-01T19:58:13Z 2019-03-01T19:58:13Z 2018 2018 Thesis http://hdl.handle.net/1721.1/120686 1088561714 eng MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission. http://dspace.mit.edu/handle/1721.1/7582 68 pages application/pdf Massachusetts Institute of Technology |
| spellingShingle | Program in Media Arts and Sciences () Alotaibi, Abdulrahman Wisdom of the machines : federated learning using OPAL |
| title | Wisdom of the machines : federated learning using OPAL |
| title_full | Wisdom of the machines : federated learning using OPAL |
| title_fullStr | Wisdom of the machines : federated learning using OPAL |
| title_full_unstemmed | Wisdom of the machines : federated learning using OPAL |
| title_short | Wisdom of the machines : federated learning using OPAL |
| title_sort | wisdom of the machines federated learning using opal |
| topic | Program in Media Arts and Sciences () |
| url | http://hdl.handle.net/1721.1/120686 |
| work_keys_str_mv | AT alotaibiabdulrahman wisdomofthemachinesfederatedlearningusingopal AT alotaibiabdulrahman federatedlearningusingopal |