Reversing uncertainty sampling to improve active learning schemes

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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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Autores principales: Cardellino, Cristian Adrián, Teruel, Milagro, Alonso i Alemany, Laura
Formato: conferenceObject
Lenguaje:Inglés
Publicado: 2021
Materias:
Natural language processing
Active learning
Acceso en línea:http://hdl.handle.net/11086/22140
Aporte de:
Repositorio Digital Universitario (UNC) de Universidad Nacional de Córdoba
id I10-R141-11086-22140
record_format dspace
spelling I10-R141-11086-221402023-08-31T13:16:28Z 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
institution Universidad Nacional de Córdoba
institution_str I-10
repository_str R-141
collection Repositorio Digital Universitario (UNC)
language Inglés
topic Natural language processing
Active learning
spellingShingle Natural language processing
Active learning
Cardellino, Cristian Adrián
Teruel, Milagro
Alonso i Alemany, Laura
Reversing uncertainty sampling to improve active learning schemes
topic_facet Natural language processing
Active learning
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
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
title Reversing uncertainty sampling to improve active learning schemes
title_short 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_sort reversing uncertainty sampling to improve active learning schemes
publishDate 2021
url http://hdl.handle.net/11086/22140
work_keys_str_mv AT cardellinocristianadrian reversinguncertaintysamplingtoimproveactivelearningschemes
AT teruelmilagro reversinguncertaintysamplingtoimproveactivelearningschemes
AT alonsoialemanylaura reversinguncertaintysamplingtoimproveactivelearningschemes
_version_ 1782014700295290880

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