Reversing uncertainty sampling to improve active learning schemes
Ponencia presentada en el 16º Simposio Argentino de Inteligencia Artificial. 44 Jornadas Argentinas de Informática. Rosario, Argentina, del 31 de agosto al 4 de septiembre de 2015.
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| Format: | conferenceObject |
| Language: | eng |
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2021
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| Online Access: | http://hdl.handle.net/11086/22140 |
| _version_ | 1801214932425900032 |
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| author | Cardellino, Cristian Adrián Teruel, Milagro Alonso i Alemany, Laura |
| author_facet | Cardellino, Cristian Adrián Teruel, Milagro Alonso i Alemany, Laura |
| author_sort | Cardellino, Cristian Adrián |
| collection | Repositorio Digital Universitario |
| description | Ponencia presentada en el 16º Simposio Argentino de Inteligencia Artificial. 44 Jornadas Argentinas de Informática. Rosario, Argentina, del 31 de agosto al 4 de septiembre de 2015. |
| format | conferenceObject |
| id | rdu-unc.22140 |
| institution | Universidad Nacional de Cordoba |
| language | eng |
| publishDate | 2021 |
| record_format | dspace |
| spelling | rdu-unc.221402023-08-31T13:16:28Z Reversing uncertainty sampling to improve active learning schemes Cardellino, Cristian Adrián Teruel, Milagro Alonso i Alemany, Laura Natural language processing Active learning Ponencia presentada en el 16º Simposio Argentino de Inteligencia Artificial. 44 Jornadas Argentinas de Informática. Rosario, Argentina, del 31 de agosto al 4 de septiembre de 2015. Fil: Cardellino, Cristian Adrián. Universidad Nacional de Córdoba. Facultad de Matemática, Astronomía y Física; Argentina. Fil: Teruel, Milagro. Universidad Nacional de Córdoba. Facultad de Matemática, Astronomía y Física; Argentina. Fil: Alonso i Alemany, Laura. Universidad Nacional de Córdoba. Facultad de Matemática, Astronomía y Física; Argentina. Active learning provides promising methods to optimize the cost of manually annotating a dataset. However, practitioners in many areas do not massively resort to such methods because they present technical difficulties and do not provide a guarantee of good performance, especially in skewed distributions with scarcely populated minority classes and an undefined, catch-all majority class, which are very common in human-related phenomena like natural language. In this paper we present a comparison of the simplest active learning technique, pool-based uncertainty sampling, and its opposite, which we call reversed uncertainty sampling. We show that both obtain results comparable to the random, arguing for a more insightful approach to active learning. http://44jaiio.sadio.org.ar/asai Fil: Cardellino, Cristian Adrián. Universidad Nacional de Córdoba. Facultad de Matemática, Astronomía y Física; Argentina. Fil: Teruel, Milagro. Universidad Nacional de Córdoba. Facultad de Matemática, Astronomía y Física; Argentina. Fil: Alonso i Alemany, Laura. Universidad Nacional de Córdoba. Facultad de Matemática, Astronomía y Física; Argentina. Ciencias de la Computación 2021-12-30T12:41:42Z 2021-12-30T12:41:42Z 2015 conferenceObject http://hdl.handle.net/11086/22140 eng Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/ Electrónico y/o Digital ISSN: 2451-7585 |
| spellingShingle | Natural language processing Active learning Cardellino, Cristian Adrián Teruel, Milagro Alonso i Alemany, Laura Reversing uncertainty sampling to improve active learning schemes |
| title | Reversing uncertainty sampling to improve active learning schemes |
| title_full | Reversing uncertainty sampling to improve active learning schemes |
| title_fullStr | Reversing uncertainty sampling to improve active learning schemes |
| title_full_unstemmed | Reversing uncertainty sampling to improve active learning schemes |
| title_short | Reversing uncertainty sampling to improve active learning schemes |
| title_sort | reversing uncertainty sampling to improve active learning schemes |
| topic | Natural language processing Active learning |
| url | http://hdl.handle.net/11086/22140 |
| work_keys_str_mv | AT cardellinocristianadrian reversinguncertaintysamplingtoimproveactivelearningschemes AT teruelmilagro reversinguncertaintysamplingtoimproveactivelearningschemes AT alonsoialemanylaura reversinguncertaintysamplingtoimproveactivelearningschemes |