[{"date_published":"2019-12-08T00:00:00Z","citation":{"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., & Bachem, O. (2019). On the fairness of disentangled representations. In Advances in Neural Information Processing Systems (Vol. 32, pp. 14611–14624). Vancouver, Canada.","ieee":"F. Locatello, G. Abbati, T. Rainforth, S. Bauer, B. Schölkopf, and O. Bachem, “On the fairness of disentangled representations,” in Advances in Neural Information Processing Systems, Vancouver, Canada, 2019, vol. 32, pp. 14611–14624.","ama":"Locatello F, Abbati G, Rainforth T, Bauer S, Schölkopf B, Bachem O. On the fairness of disentangled representations. In: Advances in Neural Information Processing Systems. Vol 32. ; 2019:14611–14624.","chicago":"Locatello, Francesco, Gabriele Abbati, Tom Rainforth, Stefan Bauer, Bernhard Schölkopf, and Olivier Bachem. “On the Fairness of Disentangled Representations.” In Advances in Neural Information Processing Systems, 32:14611–14624, 2019.","mla":"Locatello, Francesco, et al. “On the Fairness of Disentangled Representations.” Advances in Neural Information Processing Systems, 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."},"publication":"Advances in Neural Information Processing Systems","page":"14611–14624","article_processing_charge":"No","day":"08","scopus_import":"1","oa_version":"Preprint","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","_id":"14197","intvolume":" 32","title":"On the fairness of disentangled representations","status":"public","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."}],"type":"conference","conference":{"end_date":"2019-12-14","start_date":"2019-12-08","location":"Vancouver, Canada","name":"NeurIPS: Neural Information Processing Systems"},"language":[{"iso":"eng"}],"oa":1,"main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/1905.13662"}],"external_id":{"arxiv":["1905.13662"]},"quality_controlled":"1","publication_identifier":{"isbn":["9781713807933"]},"month":"12","author":[{"first_name":"Francesco","last_name":"Locatello","id":"26cfd52f-2483-11ee-8040-88983bcc06d4","orcid":"0000-0002-4850-0683","full_name":"Locatello, Francesco"},{"first_name":"Gabriele","last_name":"Abbati","full_name":"Abbati, Gabriele"},{"first_name":"Tom","last_name":"Rainforth","full_name":"Rainforth, Tom"},{"full_name":"Bauer, Stefan","last_name":"Bauer","first_name":"Stefan"},{"full_name":"Schölkopf, Bernhard","first_name":"Bernhard","last_name":"Schölkopf"},{"first_name":"Olivier","last_name":"Bachem","full_name":"Bachem, Olivier"}],"volume":32,"date_updated":"2023-09-12T09:37:22Z","date_created":"2023-08-22T14:12:28Z","year":"2019","department":[{"_id":"FrLo"}],"publication_status":"published","extern":"1"},{"scopus_import":"1","day":"29","article_processing_charge":"No","page":"14291–14301","publication":"Advances in Neural Information Processing Systems","citation":{"ista":"Locatello F, Yurtsever A, Fercoq O, Cevher V. 2019. Stochastic Frank-Wolfe for composite convex minimization. Advances in Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems vol. 32, 14291–14301.","apa":"Locatello, F., Yurtsever, A., Fercoq, O., & Cevher, V. (2019). Stochastic Frank-Wolfe for composite convex minimization. In Advances in Neural Information Processing Systems (Vol. 32, pp. 14291–14301). Vancouver, Canada.","ieee":"F. Locatello, A. Yurtsever, O. Fercoq, and V. Cevher, “Stochastic Frank-Wolfe for composite convex minimization,” in Advances in Neural Information Processing Systems, Vancouver, Canada, 2019, vol. 32, pp. 14291–14301.","ama":"Locatello F, Yurtsever A, Fercoq O, Cevher V. Stochastic Frank-Wolfe for composite convex minimization. In: Advances in Neural Information Processing Systems. Vol 32. ; 2019:14291–14301.","chicago":"Locatello, Francesco, Alp Yurtsever, Olivier Fercoq, and Volkan Cevher. “Stochastic Frank-Wolfe for Composite Convex Minimization.” In Advances in Neural Information Processing Systems, 32:14291–14301, 2019.","mla":"Locatello, Francesco, et al. “Stochastic Frank-Wolfe for Composite Convex Minimization.” Advances in Neural Information Processing Systems, vol. 32, 2019, pp. 14291–14301.","short":"F. Locatello, A. Yurtsever, O. Fercoq, V. Cevher, in:, Advances in Neural Information Processing Systems, 2019, pp. 14291–14301."},"date_published":"2019-12-29T00:00:00Z","type":"conference","abstract":[{"text":"A broad class of convex optimization problems can be formulated as a semidefinite program (SDP), minimization of a convex function over the positive-semidefinite cone subject to some affine constraints. The majority of classical SDP solvers are designed for the deterministic setting where problem data is readily available. In this setting, generalized conditional gradient methods (aka Frank-Wolfe-type methods) provide scalable solutions by leveraging the so-called linear minimization oracle instead of the projection onto the semidefinite cone. Most problems in machine learning and modern engineering applications, however, contain some degree of stochasticity. In this work, we propose the first conditional-gradient-type method for solving stochastic optimization problems under affine constraints. Our method guarantees O(k−1/3) convergence rate in expectation on the objective residual and O(k−5/12) on the feasibility gap.","lang":"eng"}],"title":"Stochastic Frank-Wolfe for composite convex minimization","status":"public","intvolume":" 32","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","_id":"14191","oa_version":"Preprint","month":"12","publication_identifier":{"isbn":["9781713807933"]},"quality_controlled":"1","oa":1,"main_file_link":[{"url":"https://arxiv.org/abs/1901.10348","open_access":"1"}],"external_id":{"arxiv":["1901.10348"]},"language":[{"iso":"eng"}],"conference":{"name":"NeurIPS: Neural Information Processing Systems","start_date":"2019-12-08","location":"Vancouver, Canada","end_date":"2019-12-14"},"extern":"1","publication_status":"published","department":[{"_id":"FrLo"}],"year":"2019","date_updated":"2023-09-12T08:48:45Z","date_created":"2023-08-22T14:09:35Z","volume":32,"author":[{"id":"26cfd52f-2483-11ee-8040-88983bcc06d4","orcid":"0000-0002-4850-0683","first_name":"Francesco","last_name":"Locatello","full_name":"Locatello, Francesco"},{"full_name":"Yurtsever, Alp","first_name":"Alp","last_name":"Yurtsever"},{"full_name":"Fercoq, Olivier","first_name":"Olivier","last_name":"Fercoq"},{"full_name":"Cevher, Volkan","last_name":"Cevher","first_name":"Volkan"}]},{"quality_controlled":"1","publication":"Advances in Neural Information Processing Systems","external_id":{"arxiv":["1905.12506"]},"citation":{"short":"S. van Steenkiste, F. Locatello, J. Schmidhuber, O. Bachem, in:, Advances in Neural Information Processing Systems, 2019.","mla":"Steenkiste, Sjoerd van, et al. “Are Disentangled Representations Helpful for Abstract Visual Reasoning?” Advances in Neural Information Processing Systems, vol. 32, 2019.","chicago":"Steenkiste, Sjoerd van, Francesco Locatello, Jürgen Schmidhuber, and Olivier Bachem. “Are Disentangled Representations Helpful for Abstract Visual Reasoning?” In Advances in Neural Information Processing Systems, Vol. 32, 2019.","ama":"Steenkiste S van, Locatello F, Schmidhuber J, Bachem O. Are disentangled representations helpful for abstract visual reasoning? In: Advances in Neural Information Processing Systems. Vol 32. ; 2019.","ieee":"S. van Steenkiste, F. Locatello, J. Schmidhuber, and O. Bachem, “Are disentangled representations helpful for abstract visual reasoning?,” in Advances in Neural Information Processing Systems, Vancouver, Canada, 2019, vol. 32.","apa":"Steenkiste, S. van, Locatello, F., Schmidhuber, J., & Bachem, O. (2019). Are disentangled representations helpful for abstract visual reasoning? In Advances in Neural Information Processing Systems (Vol. 32). Vancouver, Canada.","ista":"Steenkiste S van, Locatello F, Schmidhuber J, Bachem O. 2019. Are disentangled representations helpful for abstract visual reasoning? Advances in Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems vol. 32."},"oa":1,"main_file_link":[{"url":"https://doi.org/10.48550/arXiv.1905.12506","open_access":"1"}],"language":[{"iso":"eng"}],"conference":{"name":"NeurIPS: Neural Information Processing Systems","end_date":"2019-12-14","start_date":"2019-12-08","location":"Vancouver, Canada"},"date_published":"2019-05-29T00:00:00Z","day":"29","month":"05","article_processing_charge":"No","publication_identifier":{"isbn":["9781713807933"]},"status":"public","title":"Are disentangled representations helpful for abstract visual reasoning?","publication_status":"published","intvolume":" 32","department":[{"_id":"FrLo"}],"_id":"14193","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","year":"2019","date_created":"2023-08-22T14:09:53Z","date_updated":"2023-09-12T09:02:43Z","oa_version":"Preprint","volume":32,"author":[{"first_name":"Sjoerd van","last_name":"Steenkiste","full_name":"Steenkiste, Sjoerd van"},{"id":"26cfd52f-2483-11ee-8040-88983bcc06d4","orcid":"0000-0002-4850-0683","first_name":"Francesco","last_name":"Locatello","full_name":"Locatello, Francesco"},{"full_name":"Schmidhuber, Jürgen","last_name":"Schmidhuber","first_name":"Jürgen"},{"full_name":"Bachem, Olivier","first_name":"Olivier","last_name":"Bachem"}],"type":"conference","extern":"1","abstract":[{"text":"A disentangled representation encodes information about the salient factors\r\nof variation in the data independently. Although it is often argued that this\r\nrepresentational format is useful in learning to solve many real-world\r\ndown-stream tasks, there is little empirical evidence that supports this claim.\r\nIn this paper, we conduct a large-scale study that investigates whether\r\ndisentangled representations are more suitable for abstract reasoning tasks.\r\nUsing two new tasks similar to Raven's Progressive Matrices, we evaluate the\r\nusefulness of the representations learned by 360 state-of-the-art unsupervised\r\ndisentanglement models. Based on these representations, we train 3600 abstract\r\nreasoning models and observe that disentangled representations do in fact lead\r\nto better down-stream performance. In particular, they enable quicker learning\r\nusing fewer samples.","lang":"eng"}]},{"_id":"14200","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","intvolume":" 97","status":"public","title":"Challenging common assumptions in the unsupervised learning of disentangled representations","oa_version":"Preprint","type":"conference","abstract":[{"lang":"eng","text":"The key idea behind the unsupervised learning of disentangled representations\r\nis that real-world data is generated by a few explanatory factors of variation\r\nwhich can be recovered by unsupervised learning algorithms. In this paper, we\r\nprovide a sober look at recent progress in the field and challenge some common\r\nassumptions. We first theoretically show that the unsupervised learning of\r\ndisentangled representations is fundamentally impossible without inductive\r\nbiases on both the models and the data. Then, we train more than 12000 models\r\ncovering most prominent methods and evaluation metrics in a reproducible\r\nlarge-scale experimental study on seven different data sets. We observe that\r\nwhile the different methods successfully enforce properties ``encouraged'' by\r\nthe corresponding losses, well-disentangled models seemingly cannot be\r\nidentified without supervision. Furthermore, increased disentanglement does not\r\nseem to lead to a decreased sample complexity of learning for downstream tasks.\r\nOur results suggest that future work on disentanglement learning should be\r\nexplicit about the role of inductive biases and (implicit) supervision,\r\ninvestigate concrete benefits of enforcing disentanglement of the learned\r\nrepresentations, and consider a reproducible experimental setup covering\r\nseveral data sets."}],"citation":{"short":"F. Locatello, S. Bauer, M. Lucic, G. Rätsch, S. Gelly, B. Schölkopf, O. Bachem, in:, Proceedings of the 36th International Conference on Machine Learning, ML Research Press, 2019, pp. 4114–4124.","mla":"Locatello, Francesco, et al. “Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations.” Proceedings of the 36th International Conference on Machine Learning, vol. 97, ML Research Press, 2019, pp. 4114–24.","chicago":"Locatello, Francesco, Stefan Bauer, Mario Lucic, Gunnar Rätsch, Sylvain Gelly, Bernhard Schölkopf, and Olivier Bachem. “Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations.” In Proceedings of the 36th International Conference on Machine Learning, 97:4114–24. ML Research Press, 2019.","ama":"Locatello F, Bauer S, Lucic M, et al. Challenging common assumptions in the unsupervised learning of disentangled representations. In: Proceedings of the 36th International Conference on Machine Learning. Vol 97. ML Research Press; 2019:4114-4124.","ieee":"F. Locatello et al., “Challenging common assumptions in the unsupervised learning of disentangled representations,” in Proceedings of the 36th International Conference on Machine Learning, Long Beach, CA, United States, 2019, vol. 97, pp. 4114–4124.","apa":"Locatello, F., Bauer, S., Lucic, M., Rätsch, G., Gelly, S., Schölkopf, B., & Bachem, O. (2019). Challenging common assumptions in the unsupervised learning of disentangled representations. In Proceedings of the 36th International Conference on Machine Learning (Vol. 97, pp. 4114–4124). Long Beach, CA, United States: ML Research Press.","ista":"Locatello F, Bauer S, Lucic M, Rätsch G, Gelly S, Schölkopf B, Bachem O. 2019. Challenging common assumptions in the unsupervised learning of disentangled representations. Proceedings of the 36th International Conference on Machine Learning. International Conference on Machine Learning vol. 97, 4114–4124."},"publication":"Proceedings of the 36th International Conference on Machine Learning","page":"4114-4124","date_published":"2019-06-09T00:00:00Z","scopus_import":"1","article_processing_charge":"No","day":"09","year":"2019","publisher":"ML Research Press","department":[{"_id":"FrLo"}],"publication_status":"published","author":[{"id":"26cfd52f-2483-11ee-8040-88983bcc06d4","orcid":"0000-0002-4850-0683","first_name":"Francesco","last_name":"Locatello","full_name":"Locatello, Francesco"},{"full_name":"Bauer, Stefan","last_name":"Bauer","first_name":"Stefan"},{"full_name":"Lucic, Mario","first_name":"Mario","last_name":"Lucic"},{"full_name":"Rätsch, Gunnar","last_name":"Rätsch","first_name":"Gunnar"},{"full_name":"Gelly, Sylvain","first_name":"Sylvain","last_name":"Gelly"},{"full_name":"Schölkopf, Bernhard","first_name":"Bernhard","last_name":"Schölkopf"},{"first_name":"Olivier","last_name":"Bachem","full_name":"Bachem, Olivier"}],"volume":97,"date_updated":"2023-09-13T07:45:30Z","date_created":"2023-08-22T14:13:08Z","extern":"1","oa":1,"external_id":{"arxiv":["1811.12359"]},"main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/1811.12359"}],"quality_controlled":"1","conference":{"name":"International Conference on Machine Learning","end_date":"2019-06-15","location":"Long Beach, CA, United States","start_date":"2019-06-10"},"language":[{"iso":"eng"}],"month":"06"},{"publication_identifier":{"eissn":["1744-6848"],"issn":["1744-683X"]},"month":"01","tmp":{"name":"Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported (CC BY-NC-ND 3.0)","legal_code_url":"https://creativecommons.org/licenses/by-nc-nd/3.0/legalcode","short":"CC BY-NC-ND (3.0)","image":"/images/cc_by_nc_nd.png"},"external_id":{"pmid":["30629082"],"isi":["000457329700003"]},"oa":1,"isi":1,"quality_controlled":"1","doi":"10.1039/c8sm01956h","language":[{"iso":"eng"}],"file_date_updated":"2020-10-09T11:00:05Z","license":"https://creativecommons.org/licenses/by-nc-nd/3.0/","pmid":1,"year":"2019","publisher":"Royal Society of Chemistry","department":[{"_id":"GaTk"}],"publication_status":"published","author":[{"orcid":"0000-0001-6041-254X","id":"350F91D2-F248-11E8-B48F-1D18A9856A87","last_name":"Kavcic","first_name":"Bor","full_name":"Kavcic, Bor"},{"full_name":"Sakashita, A.","first_name":"A.","last_name":"Sakashita"},{"full_name":"Noguchi, H.","first_name":"H.","last_name":"Noguchi"},{"first_name":"P.","last_name":"Ziherl","full_name":"Ziherl, P."}],"volume":15,"date_created":"2019-01-11T07:37:47Z","date_updated":"2023-09-13T08:47:16Z","scopus_import":"1","has_accepted_license":"1","article_processing_charge":"No","day":"10","citation":{"ama":"Kavcic B, Sakashita A, Noguchi H, Ziherl P. Limiting shapes of confined lipid vesicles. Soft Matter. 2019;15(4):602-614. doi:10.1039/c8sm01956h","ieee":"B. Kavcic, A. Sakashita, H. Noguchi, and P. Ziherl, “Limiting shapes of confined lipid vesicles,” Soft Matter, vol. 15, no. 4. Royal Society of Chemistry, pp. 602–614, 2019.","apa":"Kavcic, B., Sakashita, A., Noguchi, H., & Ziherl, P. (2019). Limiting shapes of confined lipid vesicles. Soft Matter. Royal Society of Chemistry. https://doi.org/10.1039/c8sm01956h","ista":"Kavcic B, Sakashita A, Noguchi H, Ziherl P. 2019. Limiting shapes of confined lipid vesicles. Soft Matter. 15(4), 602–614.","short":"B. Kavcic, A. Sakashita, H. Noguchi, P. Ziherl, Soft Matter 15 (2019) 602–614.","mla":"Kavcic, Bor, et al. “Limiting Shapes of Confined Lipid Vesicles.” Soft Matter, vol. 15, no. 4, Royal Society of Chemistry, 2019, pp. 602–14, doi:10.1039/c8sm01956h.","chicago":"Kavcic, Bor, A. Sakashita, H. Noguchi, and P. Ziherl. “Limiting Shapes of Confined Lipid Vesicles.” Soft Matter. Royal Society of Chemistry, 2019. https://doi.org/10.1039/c8sm01956h."},"publication":"Soft Matter","page":"602-614","article_type":"original","date_published":"2019-01-10T00:00:00Z","type":"journal_article","issue":"4","abstract":[{"text":"We theoretically study the shapes of lipid vesicles confined to a spherical cavity, elaborating a framework based on the so-called limiting shapes constructed from geometrically simple structural elements such as double-membrane walls and edges. Partly inspired by numerical results, the proposed non-compartmentalized and compartmentalized limiting shapes are arranged in the bilayer-couple phase diagram which is then compared to its free-vesicle counterpart. We also compute the area-difference-elasticity phase diagram of the limiting shapes and we use it to interpret shape transitions experimentally observed in vesicles confined within another vesicle. The limiting-shape framework may be generalized to theoretically investigate the structure of certain cell organelles such as the mitochondrion.","lang":"eng"}],"_id":"5817","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","intvolume":" 15","status":"public","ddc":["530"],"title":"Limiting shapes of confined lipid vesicles","oa_version":"Submitted Version","file":[{"checksum":"614c337d6424ccd3d48d1b1f9513510d","success":1,"date_updated":"2020-10-09T11:00:05Z","date_created":"2020-10-09T11:00:05Z","relation":"main_file","file_id":"8641","file_size":5370762,"content_type":"application/pdf","creator":"bkavcic","access_level":"open_access","file_name":"lmt_sftmtr_V8.pdf"}]}]