dc.contributor.author | Cardellino, Cristian Adrián | |
dc.contributor.author | Teruel, Milagro | |
dc.contributor.author | Alonso i Alemany, Laura | |
dc.date.accessioned | 2021-12-30T12:41:42Z | |
dc.date.available | 2021-12-30T12:41:42Z | |
dc.date.issued | 2015 | |
dc.identifier.uri | http://hdl.handle.net/11086/22140 | |
dc.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. | es |
dc.description.abstract | 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. | en |
dc.description.uri | http://44jaiio.sadio.org.ar/asai | |
dc.format.medium | Electrónico y/o Digital | |
dc.language.iso | eng | es |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 International | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.source | ISSN: 2451-7585 | |
dc.subject | Natural language processing | en |
dc.subject | Active learning | en |
dc.title | Reversing uncertainty sampling to improve active learning schemes | en |
dc.type | conferenceObject | es |
dc.description.fil | Fil: Cardellino, Cristian Adrián. Universidad Nacional de Córdoba. Facultad de Matemática, Astronomía y Física; Argentina. | es |
dc.description.fil | Fil: Teruel, Milagro. Universidad Nacional de Córdoba. Facultad de Matemática, Astronomía y Física; Argentina. | es |
dc.description.fil | Fil: Alonso i Alemany, Laura. Universidad Nacional de Córdoba. Facultad de Matemática, Astronomía y Física; Argentina. | es |
dc.description.field | Ciencias de la Computación | |
dc.conference.city | Rosario | |
dc.conference.country | Argentina | |
dc.conference.editorial | Sociedad Argentina de Informática e Investigación Operativa | |
dc.conference.event | 16º Simposio Argentino de Inteligencia Artificial. 44 Jornadas Argentinas de Informática | |
dc.conference.eventcity | Rosario | |
dc.conference.eventcountry | Argentina | |
dc.conference.eventdate | 2015 | |
dc.conference.institution | Universidad Nacional de Rosario. Facultad de Ciencias Exactas, Ingeniería y Agrimensura | |
dc.conference.journal | Proceedings of ASAI 2015
Argentine Symposium on Artificial Intelligence | |
dc.conference.publication | Revista | |
dc.conference.work | Artículo Completo | |
dc.conference.type | Simposio | |