date: 2022-05-11T08:42:34Z pdf:PDFVersion: 1.7 pdf:docinfo:title: Don?t Throw it Away! The Utility of Unlabeled Data in Fair Decision Making xmp:CreatorTool: LaTeX with acmart 2022/02/19 v1.83 Typesetting articles for the Association for Computing Machinery and hyperref 2018/02/06 v6.86b Hypertext links for LaTeX access_permission:can_print_degraded: true subject: - Computing methodologies -> Machine learning algorithms; Online learning settings; - Social and professional topics; language: en dc:format: application/pdf; version=1.7 pdf:docinfo:creator_tool: LaTeX with acmart 2022/02/19 v1.83 Typesetting articles for the Association for Computing Machinery and hyperref 2018/02/06 v6.86b Hypertext links for LaTeX access_permission:fill_in_form: true pdf:encrypted: false dc:title: Don?t Throw it Away! The Utility of Unlabeled Data in Fair Decision Making modified: 2022-05-11T08:42:34Z cp:subject: - Computing methodologies -> Machine learning algorithms; Online learning settings; - Social and professional topics; pdf:docinfo:subject: - Computing methodologies -> Machine learning algorithms; Online learning settings; - Social and professional topics; pdf:docinfo:creator: Miriam Rateike, Ayan Majumdar, Olga Mineeva, Krishna P. Gummadi, Isabel Valera PTEX.Fullbanner: This is pdfTeX, Version 3.14159265-2.6-1.40.19 (TeX Live 2018/W32TeX) kpathsea version 6.3.0 meta:author: Miriam Rateike trapped: False meta:creation-date: 2022-05-11T08:42:34Z created: 2022-05-11T08:42:34Z access_permission:extract_for_accessibility: true Creation-Date: 2022-05-11T08:42:34Z Author: Miriam Rateike producer: pdfTeX-1.40.19 pdf:docinfo:producer: pdfTeX-1.40.19 pdf:unmappedUnicodeCharsPerPage: 0 dc:description: - Computing methodologies -> Machine learning algorithms; Online learning settings; - Social and professional topics; Keywords: fairness, decision making, label bias, selection bias, variational autoencoder, fair representation access_permission:modify_annotations: true dc:creator: Miriam Rateike description: - Computing methodologies -> Machine learning algorithms; Online learning settings; - Social and professional topics; dcterms:created: 2022-05-11T08:42:34Z Last-Modified: 2022-05-11T08:42:34Z dcterms:modified: 2022-05-11T08:42:34Z title: Don?t Throw it Away! The Utility of Unlabeled Data in Fair Decision Making xmpMM:DocumentID: uuid:fd182054-6205-4f26-84c9-b6c90ae4c9b1 Last-Save-Date: 2022-05-11T08:42:34Z pdf:docinfo:keywords: fairness, decision making, label bias, selection bias, variational autoencoder, fair representation pdf:docinfo:modified: 2022-05-11T08:42:34Z meta:save-date: 2022-05-11T08:42:34Z pdf:docinfo:custom:PTEX.Fullbanner: This is pdfTeX, Version 3.14159265-2.6-1.40.19 (TeX Live 2018/W32TeX) kpathsea version 6.3.0 Content-Type: application/pdf X-Parsed-By: org.apache.tika.parser.DefaultParser creator: Miriam Rateike dc:language: en dc:subject: fairness, decision making, label bias, selection bias, variational autoencoder, fair representation access_permission:assemble_document: true xmpTPg:NPages: 13 pdf:charsPerPage: 4131 access_permission:extract_content: true access_permission:can_print: true pdf:docinfo:trapped: False meta:keyword: fairness, decision making, label bias, selection bias, variational autoencoder, fair representation access_permission:can_modify: true pdf:docinfo:created: 2022-05-11T08:42:34Z