{"year":"2019","intvolume":"        32","volume":32,"_id":"14197","language":[{"iso":"eng"}],"conference":{"location":"Vancouver, Canada","end_date":"2019-12-14","name":"NeurIPS: Neural Information Processing Systems","start_date":"2019-12-08"},"citation":{"ieee":"F. Locatello, G. Abbati, T. Rainforth, S. Bauer, B. Schölkopf, and O. Bachem, “On the fairness of disentangled representations,” in <i>Advances in Neural Information Processing Systems</i>, Vancouver, Canada, 2019, vol. 32, pp. 14611–14624.","mla":"Locatello, Francesco, et al. “On the Fairness of Disentangled Representations.” <i>Advances in Neural Information Processing Systems</i>, vol. 32, 2019, pp. 14611–14624.","short":"F. Locatello, G. Abbati, T. Rainforth, S. Bauer, B. Schölkopf, O. Bachem, in:, Advances in Neural Information Processing Systems, 2019, pp. 14611–14624.","ista":"Locatello F, Abbati G, Rainforth T, Bauer S, Schölkopf B, Bachem O. 2019. On the fairness of disentangled representations. Advances in Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems vol. 32, 14611–14624.","apa":"Locatello, F., Abbati, G., Rainforth, T., Bauer, S., Schölkopf, B., &#38; Bachem, O. (2019). On the fairness of disentangled representations. In <i>Advances in Neural Information Processing Systems</i> (Vol. 32, pp. 14611–14624). Vancouver, Canada.","chicago":"Locatello, Francesco, Gabriele Abbati, Tom Rainforth, Stefan Bauer, Bernhard Schölkopf, and Olivier Bachem. “On the Fairness of Disentangled Representations.” In <i>Advances in Neural Information Processing Systems</i>, 32:14611–14624, 2019.","ama":"Locatello F, Abbati G, Rainforth T, Bauer S, Schölkopf B, Bachem O. On the fairness of disentangled representations. In: <i>Advances in Neural Information Processing Systems</i>. Vol 32. ; 2019:14611–14624."},"external_id":{"arxiv":["1905.13662"]},"publication_identifier":{"isbn":["9781713807933"]},"author":[{"orcid":"0000-0002-4850-0683","full_name":"Locatello, Francesco","id":"26cfd52f-2483-11ee-8040-88983bcc06d4","last_name":"Locatello","first_name":"Francesco"},{"full_name":"Abbati, Gabriele","first_name":"Gabriele","last_name":"Abbati"},{"last_name":"Rainforth","first_name":"Tom","full_name":"Rainforth, Tom"},{"last_name":"Bauer","first_name":"Stefan","full_name":"Bauer, Stefan"},{"full_name":"Schölkopf, Bernhard","first_name":"Bernhard","last_name":"Schölkopf"},{"first_name":"Olivier","last_name":"Bachem","full_name":"Bachem, Olivier"}],"publication":"Advances in Neural Information Processing Systems","page":"14611–14624","title":"On the fairness of disentangled representations","quality_controlled":"1","status":"public","scopus_import":"1","oa_version":"Preprint","oa":1,"date_created":"2023-08-22T14:12:28Z","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","department":[{"_id":"FrLo"}],"abstract":[{"lang":"eng","text":"Recently there has been a significant interest in learning disentangled\r\nrepresentations, as they promise increased interpretability, generalization to\r\nunseen scenarios and faster learning on downstream tasks. In this paper, we\r\ninvestigate the usefulness of different notions of disentanglement for\r\nimproving the fairness of downstream prediction tasks based on representations.\r\nWe consider the setting where the goal is to predict a target variable based on\r\nthe learned representation of high-dimensional observations (such as images)\r\nthat depend on both the target variable and an \\emph{unobserved} sensitive\r\nvariable. We show that in this setting both the optimal and empirical\r\npredictions can be unfair, even if the target variable and the sensitive\r\nvariable are independent. Analyzing the representations of more than\r\n\\num{12600} trained state-of-the-art disentangled models, we observe that\r\nseveral disentanglement scores are consistently correlated with increased\r\nfairness, suggesting that disentanglement may be a useful property to encourage\r\nfairness when sensitive variables are not observed."}],"main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/1905.13662"}],"date_published":"2019-12-08T00:00:00Z","publication_status":"published","extern":"1","article_processing_charge":"No","month":"12","date_updated":"2023-09-12T09:37:22Z","type":"conference","day":"08"}