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M., Heindorf, S., Balke, S., Haupt, J., Voigt, M., Walter, C., Witter, F., &#38; Ngonga Ngomo, A.-C. (2022). Tab2Onto: Unsupervised Semantification with Knowledge Graph Embeddings. In P. Groth, A. Rula, J. Schneider, I. Tiddi, E. Simperl, P. Alexopoulos, R. Hoekstra, M. Alam, A. Dimou, &#38; M. Tamper (Eds.), <i>The Semantic Web: ESWC 2022 Satellite Events - Hersonissos, Crete, Greece, May 29 - June 2, 2022, Proceedings</i> (Vol. 13384, pp. 47–51). Springer. <a href=\"https://doi.org/10.1007/978-3-031-11609-4_9\">https://doi.org/10.1007/978-3-031-11609-4_9</a>","ieee":"H. M. 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(2022). <i>Evaluating database systems relying on secure multiparty computation</i>.","bibtex":"@book{Anonymous_2022, title={Evaluating database systems relying on secure multiparty computation}, author={Anonymous, A}, year={2022} }","ama":"Anonymous A. <i>Evaluating Database Systems Relying on Secure Multiparty Computation</i>.; 2022.","mla":"Anonymous, A. <i>Evaluating Database Systems Relying on Secure Multiparty Computation</i>. 2022."},"project":[{"name":"SFB 901: SFB 901","_id":"1"},{"name":"SFB 901 - C: SFB 901 - Project Area C","_id":"4"},{"_id":"13","name":"SFB 901 - C1: SFB 901 - Subproject C1"}],"date_created":"2022-12-24T00:14:34Z","type":"bachelorsthesis","department":[{"_id":"34"},{"_id":"64"}],"status":"public","title":"Evaluating database systems relying on secure multiparty computation","year":"2022","author":[{"full_name":"Anonymous, A","last_name":"Anonymous","first_name":"A"}],"date_updated":"2023-01-10T10:31:35Z","_id":"34962","language":[{"iso":"eng"}],"user_id":"41047"},{"status":"public","title":"Cost of Privacy-preserving SMPC Protocols for NN-Based Inference","year":"2022","author":[{"full_name":"Anonymous, A","last_name":"Anonymous","first_name":"A"}],"date_updated":"2023-01-10T10:31:49Z","_id":"34963","language":[{"iso":"eng"}],"user_id":"41047","citation":{"mla":"Anonymous, A. <i>Cost of Privacy-Preserving SMPC Protocols for NN-Based Inference</i>. 2022.","ama":"Anonymous A. <i>Cost of Privacy-Preserving SMPC Protocols for NN-Based Inference</i>.; 2022.","bibtex":"@book{Anonymous_2022, title={Cost of Privacy-preserving SMPC Protocols for NN-Based Inference}, author={Anonymous, A}, year={2022} }","apa":"Anonymous, A. (2022). <i>Cost of Privacy-preserving SMPC Protocols for NN-Based Inference</i>.","ieee":"A. Anonymous, <i>Cost of Privacy-preserving SMPC Protocols for NN-Based Inference</i>. 2022.","short":"A. Anonymous, Cost of Privacy-Preserving SMPC Protocols for NN-Based Inference, 2022.","chicago":"Anonymous, A. <i>Cost of Privacy-Preserving SMPC Protocols for NN-Based Inference</i>, 2022."},"supervisor":[{"id":"23","first_name":"Johannes","last_name":"Blömer","full_name":"Blömer, Johannes"}],"project":[{"_id":"1","name":"SFB 901: SFB 901"},{"name":"SFB 901 - C: SFB 901 - Project Area C","_id":"4"},{"name":"SFB 901 - C1: SFB 901 - Subproject C1","_id":"13"}],"date_created":"2022-12-24T00:16:39Z","type":"mastersthesis","department":[{"_id":"34"},{"_id":"64"}]},{"date_created":"2023-01-10T10:39:27Z","type":"bachelorsthesis","department":[{"_id":"64"}],"supervisor":[{"first_name":"Johannes","last_name":"Blömer","full_name":"Blömer, Johannes"}],"citation":{"bibtex":"@book{Lohse_2022, title={Lattice Revocation Mechanisms}, author={Lohse, Jan}, year={2022} }","ama":"Lohse J. <i>Lattice Revocation Mechanisms</i>.; 2022.","mla":"Lohse, Jan. <i>Lattice Revocation Mechanisms</i>. 2022.","short":"J. Lohse, Lattice Revocation Mechanisms, 2022.","chicago":"Lohse, Jan. <i>Lattice Revocation Mechanisms</i>, 2022.","ieee":"J. Lohse, <i>Lattice Revocation Mechanisms</i>. 2022.","apa":"Lohse, J. (2022). <i>Lattice Revocation Mechanisms</i>."},"language":[{"iso":"eng"}],"_id":"35772","user_id":"47434","status":"public","title":"Lattice Revocation Mechanisms","year":"2022","author":[{"full_name":"Lohse, Jan","first_name":"Jan","last_name":"Lohse"}],"date_updated":"2023-01-10T11:54:43Z"},{"date_updated":"2023-01-11T15:20:40Z","has_accepted_license":"1","title":"Schlussbericht ITS.ML: Intelligente Technische Systeme der nächsten Generation durch Maschinelles Lernen. Forschungsvorhaben zur automatisierten Analyse von Daten mittels Maschinellen Lernens","status":"public","year":"2022","author":[{"last_name":"Hammer","first_name":"Barbara","full_name":"Hammer, Barbara"},{"full_name":"Hüllermeier, Eyke","first_name":"Eyke","last_name":"Hüllermeier","id":"48129"},{"first_name":"Volker","last_name":"Lohweg","full_name":"Lohweg, Volker"},{"full_name":"Schneider, Alexander","first_name":"Alexander","last_name":"Schneider"},{"first_name":"Wolfram","last_name":"Schenck","full_name":"Schenck, Wolfram"},{"last_name":"Kuhl","first_name":"Ulrike","full_name":"Kuhl, Ulrike"},{"full_name":"Braun, Marco","first_name":"Marco","last_name":"Braun"},{"full_name":"Pfeifer, Anton","last_name":"Pfeifer","first_name":"Anton"},{"full_name":"Holst, Christoph-Alexander","last_name":"Holst","first_name":"Christoph-Alexander"},{"full_name":"Schmidt, Malte","last_name":"Schmidt","first_name":"Malte"},{"full_name":"Schomaker, Gunnar","first_name":"Gunnar","last_name":"Schomaker"},{"id":"40795","full_name":"Tornede, Tanja","first_name":"Tanja","last_name":"Tornede"}],"doi":"10.4119/unibi/2965622","ddc":["004"],"user_id":"40795","_id":"36227","language":[{"iso":"ger"}],"citation":{"bibtex":"@book{Hammer_Hüllermeier_Lohweg_Schneider_Schenck_Kuhl_Braun_Pfeifer_Holst_Schmidt_et al._2022, title={Schlussbericht ITS.ML: Intelligente Technische Systeme der nächsten Generation durch Maschinelles Lernen. Forschungsvorhaben zur automatisierten Analyse von Daten mittels Maschinellen Lernens}, DOI={<a href=\"https://doi.org/10.4119/unibi/2965622\">10.4119/unibi/2965622</a>}, author={Hammer, Barbara and Hüllermeier, Eyke and Lohweg, Volker and Schneider, Alexander and Schenck, Wolfram and Kuhl, Ulrike and Braun, Marco and Pfeifer, Anton and Holst, Christoph-Alexander and Schmidt, Malte and et al.}, year={2022} }","chicago":"Hammer, Barbara, Eyke Hüllermeier, Volker Lohweg, Alexander Schneider, Wolfram Schenck, Ulrike Kuhl, Marco Braun, et al. <i>Schlussbericht ITS.ML: Intelligente Technische Systeme der nächsten Generation durch Maschinelles Lernen. Forschungsvorhaben zur automatisierten Analyse von Daten mittels Maschinellen Lernens</i>, 2022. <a href=\"https://doi.org/10.4119/unibi/2965622\">https://doi.org/10.4119/unibi/2965622</a>.","ama":"Hammer B, Hüllermeier E, Lohweg V, et al. <i>Schlussbericht ITS.ML: Intelligente Technische Systeme der nächsten Generation durch Maschinelles Lernen. Forschungsvorhaben zur automatisierten Analyse von Daten mittels Maschinellen Lernens</i>.; 2022. doi:<a href=\"https://doi.org/10.4119/unibi/2965622\">10.4119/unibi/2965622</a>","short":"B. Hammer, E. Hüllermeier, V. Lohweg, A. Schneider, W. Schenck, U. Kuhl, M. Braun, A. Pfeifer, C.-A. Holst, M. Schmidt, G. Schomaker, T. Tornede, Schlussbericht ITS.ML: Intelligente Technische Systeme der nächsten Generation durch Maschinelles Lernen. Forschungsvorhaben zur automatisierten Analyse von Daten mittels Maschinellen Lernens, 2022.","ieee":"B. Hammer <i>et al.</i>, <i>Schlussbericht ITS.ML: Intelligente Technische Systeme der nächsten Generation durch Maschinelles Lernen. Forschungsvorhaben zur automatisierten Analyse von Daten mittels Maschinellen Lernens</i>. 2022.","mla":"Hammer, Barbara, et al. <i>Schlussbericht ITS.ML: Intelligente Technische Systeme der nächsten Generation durch Maschinelles Lernen. Forschungsvorhaben zur automatisierten Analyse von Daten mittels Maschinellen Lernens</i>. 2022, doi:<a href=\"https://doi.org/10.4119/unibi/2965622\">10.4119/unibi/2965622</a>.","apa":"Hammer, B., Hüllermeier, E., Lohweg, V., Schneider, A., Schenck, W., Kuhl, U., Braun, M., Pfeifer, A., Holst, C.-A., Schmidt, M., Schomaker, G., &#38; Tornede, T. (2022). <i>Schlussbericht ITS.ML: Intelligente Technische Systeme der nächsten Generation durch Maschinelles Lernen. Forschungsvorhaben zur automatisierten Analyse von Daten mittels Maschinellen Lernens</i>. <a href=\"https://doi.org/10.4119/unibi/2965622\">https://doi.org/10.4119/unibi/2965622</a>"},"type":"report","department":[{"_id":"34"},{"_id":"7"},{"_id":"534"}],"date_created":"2023-01-11T15:00:00Z"},{"date_updated":"2023-10-09T04:17:29Z","publication_status":"published","author":[{"last_name":"Gharibian","first_name":"Sevag","orcid":"0000-0002-9992-3379","full_name":"Gharibian, Sevag","id":"71541"},{"full_name":"Gall, François Le","last_name":"Gall","first_name":"François Le"}],"title":"Dequantizing the Quantum Singular Value Transformation: Hardness and  Applications to Quantum Chemistry and the Quantum PCP Conjecture","status":"public","year":"2022","user_id":"71541","_id":"27531","language":[{"iso":"eng"}],"page":"19-32","main_file_link":[{"url":"https://arxiv.org/abs/2111.09079","open_access":"1"}],"abstract":[{"text":"The Quantum Singular Value Transformation (QSVT) is a recent technique that\r\ngives a unified framework to describe most quantum algorithms discovered so\r\nfar, and may lead to the development of novel quantum algorithms. In this paper\r\nwe investigate the hardness of classically simulating the QSVT. A recent result\r\nby Chia, Gily\\'en, Li, Lin, Tang and Wang (STOC 2020) showed that the QSVT can\r\nbe efficiently \"dequantized\" for low-rank matrices, and discussed its\r\nimplication to quantum machine learning. In this work, motivated by\r\nestablishing the superiority of quantum algorithms for quantum chemistry and\r\nmaking progress on the quantum PCP conjecture, we focus on the other main class\r\nof matrices considered in applications of the QSVT, sparse matrices.\r\n  We first show how to efficiently \"dequantize\", with arbitrarily small\r\nconstant precision, the QSVT associated with a low-degree polynomial. We apply\r\nthis technique to design classical algorithms that estimate, with constant\r\nprecision, the singular values of a sparse matrix. We show in particular that a\r\ncentral computational problem considered by quantum algorithms for quantum\r\nchemistry (estimating the ground state energy of a local Hamiltonian when\r\ngiven, as an additional input, a state sufficiently close to the ground state)\r\ncan be solved efficiently with constant precision on a classical computer. As a\r\ncomplementary result, we prove that with inverse-polynomial precision, the same\r\nproblem becomes BQP-complete. This gives theoretical evidence for the\r\nsuperiority of quantum algorithms for chemistry, and strongly suggests that\r\nsaid superiority stems from the improved precision achievable in the quantum\r\nsetting. We also discuss how this dequantization technique may help make\r\nprogress on the central quantum PCP conjecture.","lang":"eng"}],"citation":{"ieee":"S. Gharibian and F. L. Gall, “Dequantizing the Quantum Singular Value Transformation: Hardness and  Applications to Quantum Chemistry and the Quantum PCP Conjecture,” in <i>Proceedings of the 54th ACM Symposium on Theory of Computing (STOC)</i>, 2022, pp. 19–32.","apa":"Gharibian, S., &#38; Gall, F. L. (2022). Dequantizing the Quantum Singular Value Transformation: Hardness and  Applications to Quantum Chemistry and the Quantum PCP Conjecture. <i>Proceedings of the 54th ACM Symposium on Theory of Computing (STOC)</i>, 19–32.","mla":"Gharibian, Sevag, and François Le Gall. “Dequantizing the Quantum Singular Value Transformation: Hardness and  Applications to Quantum Chemistry and the Quantum PCP Conjecture.” <i>Proceedings of the 54th ACM Symposium on Theory of Computing (STOC)</i>, 2022, pp. 19–32.","bibtex":"@inproceedings{Gharibian_Gall_2022, title={Dequantizing the Quantum Singular Value Transformation: Hardness and  Applications to Quantum Chemistry and the Quantum PCP Conjecture}, booktitle={Proceedings of the 54th ACM Symposium on Theory of Computing (STOC)}, author={Gharibian, Sevag and Gall, François Le}, year={2022}, pages={19–32} }","ama":"Gharibian S, Gall FL. Dequantizing the Quantum Singular Value Transformation: Hardness and  Applications to Quantum Chemistry and the Quantum PCP Conjecture. In: <i>Proceedings of the 54th ACM Symposium on Theory of Computing (STOC)</i>. ; 2022:19-32.","short":"S. Gharibian, F.L. Gall, in: Proceedings of the 54th ACM Symposium on Theory of Computing (STOC), 2022, pp. 19–32.","chicago":"Gharibian, Sevag, and François Le Gall. “Dequantizing the Quantum Singular Value Transformation: Hardness and  Applications to Quantum Chemistry and the Quantum PCP Conjecture.” In <i>Proceedings of the 54th ACM Symposium on Theory of Computing (STOC)</i>, 19–32, 2022."},"publication":"Proceedings of the 54th ACM Symposium on Theory of Computing (STOC)","oa":"1","department":[{"_id":"623"},{"_id":"7"}],"type":"conference","date_created":"2021-11-18T07:32:56Z","external_id":{"arxiv":["2111.09079"]}},{"type":"book_chapter","department":[{"_id":"819"},{"_id":"34"}],"date_created":"2023-08-04T07:03:47Z","place":"Wiesbaden","publication":"Hate Speech — Definitionen, Ausprägungen, Lösungen","citation":{"short":"M. Niemann, D. Assenmacher, J. Brunk, D.M. Riehle, J. Becker, H. Trautmann, in: G. Weitzel, S. Mündges (Eds.), Hate Speech — Definitionen, Ausprägungen, Lösungen, VS Verlag für Sozialwissenschaften, Wiesbaden, 2022, pp. 249–274.","chicago":"Niemann, Marco, Dennis Assenmacher, Jens Brunk, Dennis Maximilian Riehle, Jörg Becker, and Heike Trautmann. “(Semi-)Automatische Kommentarmoderation Zur Erhaltung Konstruktiver Diskurse.” In <i>Hate Speech — Definitionen, Ausprägungen, Lösungen</i>, edited by Gerrit Weitzel and Stephan Mündges, 249–274. Wiesbaden: VS Verlag für Sozialwissenschaften, 2022. <a href=\"https://doi.org/10.1007/978-3-658-35658-3_13\">https://doi.org/10.1007/978-3-658-35658-3_13</a>.","ieee":"M. Niemann, D. Assenmacher, J. Brunk, D. M. Riehle, J. Becker, and H. Trautmann, “(Semi-)Automatische Kommentarmoderation zur Erhaltung Konstruktiver Diskurse,” in <i>Hate Speech — Definitionen, Ausprägungen, Lösungen</i>, G. Weitzel and S. Mündges, Eds. Wiesbaden: VS Verlag für Sozialwissenschaften, 2022, pp. 249–274.","apa":"Niemann, M., Assenmacher, D., Brunk, J., Riehle, D. M., Becker, J., &#38; Trautmann, H. (2022). (Semi-)Automatische Kommentarmoderation zur Erhaltung Konstruktiver Diskurse. In G. Weitzel &#38; S. Mündges (Eds.), <i>Hate Speech — Definitionen, Ausprägungen, Lösungen</i> (pp. 249–274). VS Verlag für Sozialwissenschaften. <a href=\"https://doi.org/10.1007/978-3-658-35658-3_13\">https://doi.org/10.1007/978-3-658-35658-3_13</a>","bibtex":"@inbook{Niemann_Assenmacher_Brunk_Riehle_Becker_Trautmann_2022, place={Wiesbaden}, title={(Semi-)Automatische Kommentarmoderation zur Erhaltung Konstruktiver Diskurse}, DOI={<a href=\"https://doi.org/10.1007/978-3-658-35658-3_13\">10.1007/978-3-658-35658-3_13</a>}, booktitle={Hate Speech — Definitionen, Ausprägungen, Lösungen}, publisher={VS Verlag für Sozialwissenschaften}, author={Niemann, Marco and Assenmacher, Dennis and Brunk, Jens and Riehle, Dennis Maximilian and Becker, Jörg and Trautmann, Heike}, editor={Weitzel, Gerrit and Mündges, Stephan}, year={2022}, pages={249–274} }","ama":"Niemann M, Assenmacher D, Brunk J, Riehle DM, Becker J, Trautmann H. (Semi-)Automatische Kommentarmoderation zur Erhaltung Konstruktiver Diskurse. In: Weitzel G, Mündges S, eds. <i>Hate Speech — Definitionen, Ausprägungen, Lösungen</i>. VS Verlag für Sozialwissenschaften; 2022:249–274. doi:<a href=\"https://doi.org/10.1007/978-3-658-35658-3_13\">10.1007/978-3-658-35658-3_13</a>","mla":"Niemann, Marco, et al. “(Semi-)Automatische Kommentarmoderation Zur Erhaltung Konstruktiver Diskurse.” <i>Hate Speech — Definitionen, Ausprägungen, Lösungen</i>, edited by Gerrit Weitzel and Stephan Mündges, VS Verlag für Sozialwissenschaften, 2022, pp. 249–274, doi:<a href=\"https://doi.org/10.1007/978-3-658-35658-3_13\">10.1007/978-3-658-35658-3_13</a>."},"user_id":"15504","doi":"10.1007/978-3-658-35658-3_13","editor":[{"full_name":"Weitzel, Gerrit","last_name":"Weitzel","first_name":"Gerrit"},{"full_name":"Mündges, Stephan","last_name":"Mündges","first_name":"Stephan"}],"page":"249–274","publisher":"VS Verlag für Sozialwissenschaften","_id":"46300","language":[{"iso":"eng"}],"date_updated":"2023-10-16T12:35:41Z","title":"(Semi-)Automatische Kommentarmoderation zur Erhaltung Konstruktiver Diskurse","status":"public","year":"2022","publication_identifier":{"isbn":["978-3-658-35658-3"]},"author":[{"first_name":"Marco","last_name":"Niemann","full_name":"Niemann, Marco"},{"first_name":"Dennis","last_name":"Assenmacher","full_name":"Assenmacher, Dennis"},{"first_name":"Jens","last_name":"Brunk","full_name":"Brunk, Jens"},{"full_name":"Riehle, Dennis Maximilian","last_name":"Riehle","first_name":"Dennis Maximilian"},{"last_name":"Becker","first_name":"Jörg","full_name":"Becker, Jörg"},{"id":"100740","full_name":"Trautmann, Heike","orcid":"0000-0002-9788-8282","first_name":"Heike","last_name":"Trautmann"}]},{"author":[{"last_name":"Assenmacher","first_name":"D","full_name":"Assenmacher, D"},{"full_name":"Trautmann, Heike","first_name":"Heike","last_name":"Trautmann","orcid":"0000-0002-9788-8282","id":"100740"}],"title":"Textual One-Pass Stream Clustering with Automated Distance Threshold Adaption","year":"2022","status":"public","date_updated":"2023-10-16T12:35:22Z","_id":"46301","language":[{"iso":"eng"}],"publisher":"Springer International Publishing","page":"3–16","editor":[{"first_name":"T","last_name":"et al. Tran","full_name":"et al. Tran, T"}],"user_id":"15504","doi":"10.1007/978-3-031-21743-2_1","citation":{"short":"D. Assenmacher, H. Trautmann, in: T. et al. Tran (Ed.), Intelligent Information and Database Systems, Springer International Publishing, Cham, 2022, pp. 3–16.","chicago":"Assenmacher, D, and Heike Trautmann. “Textual One-Pass Stream Clustering with Automated Distance Threshold Adaption.” In <i>Intelligent Information and Database Systems</i>, edited by T et al. Tran, 3–16. Cham: Springer International Publishing, 2022. <a href=\"https://doi.org/10.1007/978-3-031-21743-2_1\">https://doi.org/10.1007/978-3-031-21743-2_1</a>.","ieee":"D. Assenmacher and H. Trautmann, “Textual One-Pass Stream Clustering with Automated Distance Threshold Adaption,” in <i>Intelligent Information and Database Systems</i>, 2022, pp. 3–16, doi: <a href=\"https://doi.org/10.1007/978-3-031-21743-2_1\">10.1007/978-3-031-21743-2_1</a>.","apa":"Assenmacher, D., &#38; Trautmann, H. (2022). Textual One-Pass Stream Clustering with Automated Distance Threshold Adaption. In T. et al. Tran (Ed.), <i>Intelligent Information and Database Systems</i> (pp. 3–16). Springer International Publishing. <a href=\"https://doi.org/10.1007/978-3-031-21743-2_1\">https://doi.org/10.1007/978-3-031-21743-2_1</a>","bibtex":"@inproceedings{Assenmacher_Trautmann_2022, place={Cham}, title={Textual One-Pass Stream Clustering with Automated Distance Threshold Adaption}, DOI={<a href=\"https://doi.org/10.1007/978-3-031-21743-2_1\">10.1007/978-3-031-21743-2_1</a>}, booktitle={Intelligent Information and Database Systems}, publisher={Springer International Publishing}, author={Assenmacher, D and Trautmann, Heike}, editor={et al. Tran, T}, year={2022}, pages={3–16} }","ama":"Assenmacher D, Trautmann H. Textual One-Pass Stream Clustering with Automated Distance Threshold Adaption. In: et al. Tran T, ed. <i>Intelligent Information and Database Systems</i>. Springer International Publishing; 2022:3–16. doi:<a href=\"https://doi.org/10.1007/978-3-031-21743-2_1\">10.1007/978-3-031-21743-2_1</a>","mla":"Assenmacher, D., and Heike Trautmann. “Textual One-Pass Stream Clustering with Automated Distance Threshold Adaption.” <i>Intelligent Information and Database Systems</i>, edited by T et al. Tran, Springer International Publishing, 2022, pp. 3–16, doi:<a href=\"https://doi.org/10.1007/978-3-031-21743-2_1\">10.1007/978-3-031-21743-2_1</a>."},"publication":"Intelligent Information and Database Systems","date_created":"2023-08-04T07:04:54Z","place":"Cham","department":[{"_id":"819"},{"_id":"34"}],"type":"conference"},{"intvolume":"        40","date_updated":"2023-10-16T12:57:24Z","author":[{"full_name":"Assenmacher, Dennis","first_name":"Dennis","last_name":"Assenmacher"},{"first_name":"Derek","last_name":"Weber","full_name":"Weber, Derek"},{"last_name":"Preuss","first_name":"Mike","full_name":"Preuss, Mike"},{"full_name":"Valdez, André Calero","first_name":"André Calero","last_name":"Valdez"},{"full_name":"Bradshaw, Alison","last_name":"Bradshaw","first_name":"Alison"},{"full_name":"Ross, Björn","last_name":"Ross","first_name":"Björn"},{"full_name":"Cresci, Stefano","last_name":"Cresci","first_name":"Stefano"},{"last_name":"Trautmann","orcid":"0000-0002-9788-8282","first_name":"Heike","full_name":"Trautmann, Heike","id":"100740"},{"last_name":"Neumann","first_name":"Frank","full_name":"Neumann, Frank"},{"first_name":"Christian","last_name":"Grimme","full_name":"Grimme, Christian"}],"title":"Benchmarking Crisis in Social Media Analytics: A Solution for the Data-Sharing Problem","status":"public","year":"2022","volume":40,"user_id":"15504","doi":"10.1177/08944393211012268","language":[{"iso":"eng"}],"_id":"46316","page":"1496-1522","abstract":[{"lang":"eng","text":" Computational social science uses computational and statistical methods in order to evaluate social interaction. The public availability of data sets is thus a necessary precondition for reliable and replicable research. These data allow researchers to benchmark the computational methods they develop, test the generalizability of their findings, and build confidence in their results. When social media data are concerned, data sharing is often restricted for legal or privacy reasons, which makes the comparison of methods and the replicability of research results infeasible. Social media analytics research, consequently, faces an integrity crisis. How is it possible to create trust in computational or statistical analyses, when they cannot be validated by third parties? In this work, we explore this well-known, yet little discussed, problem for social media analytics. We investigate how this problem can be solved by looking at related computational research areas. Moreover, we propose and implement a prototype to address the problem in the form of a new evaluation framework that enables the comparison of algorithms without the need to exchange data directly, while maintaining flexibility for the algorithm design. "}],"citation":{"mla":"Assenmacher, Dennis, et al. “Benchmarking Crisis in Social Media Analytics: A Solution for the Data-Sharing Problem.” <i>Social Science Computer Review</i>, vol. 40, no. 6, 2022, pp. 1496–522, doi:<a href=\"https://doi.org/10.1177/08944393211012268\">10.1177/08944393211012268</a>.","bibtex":"@article{Assenmacher_Weber_Preuss_Valdez_Bradshaw_Ross_Cresci_Trautmann_Neumann_Grimme_2022, title={Benchmarking Crisis in Social Media Analytics: A Solution for the Data-Sharing Problem}, volume={40}, DOI={<a href=\"https://doi.org/10.1177/08944393211012268\">10.1177/08944393211012268</a>}, number={6}, journal={Social Science Computer Review}, author={Assenmacher, Dennis and Weber, Derek and Preuss, Mike and Valdez, André Calero and Bradshaw, Alison and Ross, Björn and Cresci, Stefano and Trautmann, Heike and Neumann, Frank and Grimme, Christian}, year={2022}, pages={1496–1522} }","ama":"Assenmacher D, Weber D, Preuss M, et al. Benchmarking Crisis in Social Media Analytics: A Solution for the Data-Sharing Problem. <i>Social Science Computer Review</i>. 2022;40(6):1496-1522. doi:<a href=\"https://doi.org/10.1177/08944393211012268\">10.1177/08944393211012268</a>","ieee":"D. Assenmacher <i>et al.</i>, “Benchmarking Crisis in Social Media Analytics: A Solution for the Data-Sharing Problem,” <i>Social Science Computer Review</i>, vol. 40, no. 6, pp. 1496–1522, 2022, doi: <a href=\"https://doi.org/10.1177/08944393211012268\">10.1177/08944393211012268</a>.","apa":"Assenmacher, D., Weber, D., Preuss, M., Valdez, A. C., Bradshaw, A., Ross, B., Cresci, S., Trautmann, H., Neumann, F., &#38; Grimme, C. (2022). Benchmarking Crisis in Social Media Analytics: A Solution for the Data-Sharing Problem. <i>Social Science Computer Review</i>, <i>40</i>(6), 1496–1522. <a href=\"https://doi.org/10.1177/08944393211012268\">https://doi.org/10.1177/08944393211012268</a>","chicago":"Assenmacher, Dennis, Derek Weber, Mike Preuss, André Calero Valdez, Alison Bradshaw, Björn Ross, Stefano Cresci, Heike Trautmann, Frank Neumann, and Christian Grimme. “Benchmarking Crisis in Social Media Analytics: A Solution for the Data-Sharing Problem.” <i>Social Science Computer Review</i> 40, no. 6 (2022): 1496–1522. <a href=\"https://doi.org/10.1177/08944393211012268\">https://doi.org/10.1177/08944393211012268</a>.","short":"D. Assenmacher, D. Weber, M. Preuss, A.C. Valdez, A. Bradshaw, B. Ross, S. Cresci, H. Trautmann, F. Neumann, C. Grimme, Social Science Computer Review 40 (2022) 1496–1522."},"publication":"Social Science Computer Review","issue":"6","department":[{"_id":"34"},{"_id":"819"}],"type":"journal_article","date_created":"2023-08-04T07:26:36Z"},{"abstract":[{"text":"Manufacturing companies are challenged to make the increasingly complex work processes equally manageable for all employees to prevent an impending loss of competence. In this contribution, an intelligent assistance system is proposed enabling employees to help themselves in the workplace and provide them with competence-related support. This results in increasing the short- and long-term efficiency of problem solving in companies.","lang":"eng"}],"related_material":{"link":[{"url":"https://ieeexplore.ieee.org/document/9921520","relation":"confirmation"}]},"project":[{"_id":"409","grant_number":"02L19C115","name":"KIAM: KIAM: Kompetenzzentrum KI in der Arbeitswelt des industriellen Mittelstands in OstWestfalenLippe"}],"citation":{"mla":"Deppe, Sahar, et al. <i>AI-Based Assistance System for Manufacturing</i>. 2022, doi:<a href=\"https://doi.org/10.1109/ETFA52439.2022.9921520\">10.1109/ETFA52439.2022.9921520</a>.","bibtex":"@article{Deppe_Brandt_Brünninghaus_Papenkordt_Heindorf_Tschirner-Vinke_2022, series={2022 IEEE 27th International Conference on Emerging Technologies and Factory Automation (ETFA)}, title={AI-Based Assistance System for Manufacturing}, DOI={<a href=\"https://doi.org/10.1109/ETFA52439.2022.9921520\">10.1109/ETFA52439.2022.9921520</a>}, author={Deppe, Sahar and Brandt, Lukas and Brünninghaus, Marc and Papenkordt, Jörg and Heindorf, Stefan and Tschirner-Vinke, Gudrun}, year={2022}, collection={2022 IEEE 27th International Conference on Emerging Technologies and Factory Automation (ETFA)} }","ama":"Deppe S, Brandt L, Brünninghaus M, Papenkordt J, Heindorf S, Tschirner-Vinke G. AI-Based Assistance System for Manufacturing. Published online 2022. doi:<a href=\"https://doi.org/10.1109/ETFA52439.2022.9921520\">10.1109/ETFA52439.2022.9921520</a>","ieee":"S. Deppe, L. Brandt, M. Brünninghaus, J. Papenkordt, S. Heindorf, and G. Tschirner-Vinke, “AI-Based Assistance System for Manufacturing.” 2022, doi: <a href=\"https://doi.org/10.1109/ETFA52439.2022.9921520\">10.1109/ETFA52439.2022.9921520</a>.","apa":"Deppe, S., Brandt, L., Brünninghaus, M., Papenkordt, J., Heindorf, S., &#38; Tschirner-Vinke, G. (2022). <i>AI-Based Assistance System for Manufacturing</i>. ETFA, Stuttgart. <a href=\"https://doi.org/10.1109/ETFA52439.2022.9921520\">https://doi.org/10.1109/ETFA52439.2022.9921520</a>","chicago":"Deppe, Sahar, Lukas Brandt, Marc Brünninghaus, Jörg Papenkordt, Stefan Heindorf, and Gudrun Tschirner-Vinke. “AI-Based Assistance System for Manufacturing.” 2022 IEEE 27th International Conference on Emerging Technologies and Factory Automation (ETFA), 2022. <a href=\"https://doi.org/10.1109/ETFA52439.2022.9921520\">https://doi.org/10.1109/ETFA52439.2022.9921520</a>.","short":"S. Deppe, L. Brandt, M. Brünninghaus, J. Papenkordt, S. Heindorf, G. Tschirner-Vinke, (2022)."},"type":"conference","keyword":["Assistance system","Knowledge graph","Information retrieval","Neural networks","AR"],"department":[{"_id":"178"},{"_id":"574"},{"_id":"184"}],"date_created":"2022-10-28T11:43:49Z","date_updated":"2023-11-23T08:07:51Z","title":"AI-Based Assistance System for Manufacturing","year":"2022","status":"public","conference":{"name":"ETFA","start_date":"2022-09-06","location":"Stuttgart","end_date":"2022-09-09"},"author":[{"full_name":"Deppe, Sahar","last_name":"Deppe","first_name":"Sahar"},{"first_name":"Lukas","last_name":"Brandt","full_name":"Brandt, Lukas"},{"last_name":"Brünninghaus","first_name":"Marc","full_name":"Brünninghaus, Marc"},{"first_name":"Jörg","last_name":"Papenkordt","full_name":"Papenkordt, Jörg","id":"44648"},{"full_name":"Heindorf, Stefan","last_name":"Heindorf","first_name":"Stefan","orcid":"0000-0002-4525-6865","id":"11871"},{"last_name":"Tschirner-Vinke","first_name":"Gudrun","full_name":"Tschirner-Vinke, Gudrun"}],"doi":"10.1109/ETFA52439.2022.9921520","user_id":"44648","language":[{"iso":"eng"}],"_id":"33957","series_title":"2022 IEEE 27th International Conference on Emerging Technologies and Factory Automation (ETFA)"},{"place":"Cham","citation":{"short":"L. Schneider, L. Schäpermeier, R.P. Prager, B. Bischl, H. Trautmann, P. Kerschke, in: G. Rudolph, A.V. Kononova, H. Aguirre, P. Kerschke, G. Ochoa, T. Tušar (Eds.), Parallel Problem Solving from Nature — PPSN XVII, Springer International Publishing, Cham, 2022, pp. 575–589.","chicago":"Schneider, Lennart, Lennart Schäpermeier, Raphael Patrick Prager, Bernd Bischl, Heike Trautmann, and Pascal Kerschke. “HPO x ELA: Investigating Hyperparameter Optimization Landscapes by Means of Exploratory Landscape Analysis.” In <i>Parallel Problem Solving from Nature — PPSN XVII</i>, edited by Günter Rudolph, Anna V. Kononova, Hernán Aguirre, Pascal Kerschke, Gabriela Ochoa, and Tea Tušar, 575–589. Cham: Springer International Publishing, 2022. <a href=\"https://doi.org/10.1007/978-3-031-14714-2_40\">https://doi.org/10.1007/978-3-031-14714-2_40</a>.","ieee":"L. Schneider, L. Schäpermeier, R. P. Prager, B. Bischl, H. Trautmann, and P. Kerschke, “HPO x ELA: Investigating Hyperparameter Optimization Landscapes by Means of Exploratory Landscape Analysis,” in <i>Parallel Problem Solving from Nature — PPSN XVII</i>, 2022, pp. 575–589, doi: <a href=\"https://doi.org/10.1007/978-3-031-14714-2_40\">10.1007/978-3-031-14714-2_40</a>.","apa":"Schneider, L., Schäpermeier, L., Prager, R. P., Bischl, B., Trautmann, H., &#38; Kerschke, P. (2022). HPO x ELA: Investigating Hyperparameter Optimization Landscapes by Means of Exploratory Landscape Analysis. In G. Rudolph, A. V. Kononova, H. Aguirre, P. Kerschke, G. Ochoa, &#38; T. Tušar (Eds.), <i>Parallel Problem Solving from Nature — PPSN XVII</i> (pp. 575–589). Springer International Publishing. <a href=\"https://doi.org/10.1007/978-3-031-14714-2_40\">https://doi.org/10.1007/978-3-031-14714-2_40</a>","bibtex":"@inproceedings{Schneider_Schäpermeier_Prager_Bischl_Trautmann_Kerschke_2022, place={Cham}, title={HPO x ELA: Investigating Hyperparameter Optimization Landscapes by Means of Exploratory Landscape Analysis}, DOI={<a href=\"https://doi.org/10.1007/978-3-031-14714-2_40\">10.1007/978-3-031-14714-2_40</a>}, booktitle={Parallel Problem Solving from Nature — PPSN XVII}, publisher={Springer International Publishing}, author={Schneider, Lennart and Schäpermeier, Lennart and Prager, Raphael Patrick and Bischl, Bernd and Trautmann, Heike and Kerschke, Pascal}, editor={Rudolph, Günter and Kononova, Anna V. and Aguirre, Hernán and Kerschke, Pascal and Ochoa, Gabriela and Tušar, Tea}, year={2022}, pages={575–589} }","ama":"Schneider L, Schäpermeier L, Prager RP, Bischl B, Trautmann H, Kerschke P. HPO x ELA: Investigating Hyperparameter Optimization Landscapes by Means of Exploratory Landscape Analysis. In: Rudolph G, Kononova AV, Aguirre H, Kerschke P, Ochoa G, Tušar T, eds. <i>Parallel Problem Solving from Nature — PPSN XVII</i>. Springer International Publishing; 2022:575–589. doi:<a href=\"https://doi.org/10.1007/978-3-031-14714-2_40\">10.1007/978-3-031-14714-2_40</a>","mla":"Schneider, Lennart, et al. “HPO x ELA: Investigating Hyperparameter Optimization Landscapes by Means of Exploratory Landscape Analysis.” <i>Parallel Problem Solving from Nature — PPSN XVII</i>, edited by Günter Rudolph et al., Springer International Publishing, 2022, pp. 575–589, doi:<a href=\"https://doi.org/10.1007/978-3-031-14714-2_40\">10.1007/978-3-031-14714-2_40</a>."},"editor":[{"last_name":"Rudolph","first_name":"Günter","full_name":"Rudolph, Günter"},{"first_name":"Anna V.","last_name":"Kononova","full_name":"Kononova, Anna V."},{"full_name":"Aguirre, Hernán","first_name":"Hernán","last_name":"Aguirre"},{"full_name":"Kerschke, Pascal","last_name":"Kerschke","first_name":"Pascal"},{"full_name":"Ochoa, Gabriela","last_name":"Ochoa","first_name":"Gabriela"},{"full_name":"Tušar, Tea","last_name":"Tušar","first_name":"Tea"}],"user_id":"15504","_id":"46306","publisher":"Springer International Publishing","page":"575–589","status":"public","department":[{"_id":"34"},{"_id":"819"}],"type":"conference","date_created":"2023-08-04T07:15:16Z","abstract":[{"text":"Hyperparameter optimization (HPO) is a key component of machine learning models for achieving peak predictive performance. While numerous methods and algorithms for HPO have been proposed over the last years, little progress has been made in illuminating and examining the actual structure of these black-box optimization problems. Exploratory landscape analysis (ELA) subsumes a set of techniques that can be used to gain knowledge about properties of unknown optimization problems. In this paper, we evaluate the performance of five different black-box optimizers on 30 HPO problems, which consist of two-, three- and five-dimensional continuous search spaces of the XGBoost learner trained on 10 different data sets. This is contrasted with the performance of the same optimizers evaluated on 360 problem instances from the black-box optimization benchmark (BBOB). We then compute ELA features on the HPO and BBOB problems and examine similarities and differences. A cluster analysis of the HPO and BBOB problems in ELA feature space allows us to identify how the HPO problems compare to the BBOB problems on a structural meta-level. We identify a subset of BBOB problems that are close to the HPO problems in ELA feature space and show that optimizer performance is comparably similar on these two sets of benchmark problems. We highlight open challenges of ELA for HPO and discuss potential directions of future research and applications.","lang":"eng"}],"publication":"Parallel Problem Solving from Nature — PPSN XVII","doi":"10.1007/978-3-031-14714-2_40","language":[{"iso":"eng"}],"date_updated":"2023-10-16T12:51:27Z","publication_identifier":{"isbn":["978-3-031-14714-2"]},"author":[{"last_name":"Schneider","first_name":"Lennart","full_name":"Schneider, Lennart"},{"first_name":"Lennart","last_name":"Schäpermeier","full_name":"Schäpermeier, Lennart"},{"first_name":"Raphael Patrick","last_name":"Prager","full_name":"Prager, Raphael Patrick"},{"full_name":"Bischl, Bernd","last_name":"Bischl","first_name":"Bernd"},{"id":"100740","last_name":"Trautmann","first_name":"Heike","orcid":"0000-0002-9788-8282","full_name":"Trautmann, Heike"},{"full_name":"Kerschke, Pascal","first_name":"Pascal","last_name":"Kerschke"}],"year":"2022","title":"HPO x ELA: Investigating Hyperparameter Optimization Landscapes by Means of Exploratory Landscape Analysis"},{"date_updated":"2023-10-16T12:52:33Z","intvolume":"         1","title":"The objective that freed me: a multi-objective local search approach for continuous single-objective optimization","status":"public","year":"2022","author":[{"last_name":"Aspar","first_name":"Pelin","full_name":"Aspar, Pelin"},{"first_name":"Vera","last_name":"Steinhoff","full_name":"Steinhoff, Vera"},{"full_name":"Schäpermeier, Lennart","last_name":"Schäpermeier","first_name":"Lennart"},{"first_name":"Pascal","last_name":"Kerschke","full_name":"Kerschke, Pascal"},{"id":"100740","full_name":"Trautmann, Heike","last_name":"Trautmann","first_name":"Heike","orcid":"0000-0002-9788-8282"},{"full_name":"Grimme, Christian","last_name":"Grimme","first_name":"Christian"}],"doi":"10.1007/s11047-022-09919-w","user_id":"15504","volume":1,"page":"1–15","language":[{"iso":"eng"}],"_id":"46308","abstract":[{"lang":"eng","text":"Single-objective continuous optimization can be challenging, especially when dealing with multimodal problems. This work sheds light on the effects that multi-objective optimization may have in the single-objective space. For this purpose, we examine the inner mechanisms of the recently developed sophisticated local search procedure SOMOGSA. This method solves multimodal single-objective continuous optimization problems based on first expanding the problem with an additional objective (e.g., a sphere function) to the bi-objective domain and subsequently exploiting local structures of the resulting landscapes. Our study particularly focuses on the sensitivity of this multiobjectivization approach w.r.t. (1) the parametrization of the artificial second objective, as well as (2) the position of the initial starting points in the search space. As SOMOGSA is a modular framework for encapsulating local search, we integrate Nelder–Mead local search as optimizer in the respective module and compare the performance of the resulting hybrid local search to its original single-objective counterpart. We show that the SOMOGSA framework can significantly boost local search by multiobjectivization. Hence, combined with more sophisticated local search and metaheuristics, this may help solve highly multimodal optimization problems in the future."}],"publication":"Natural Computing","citation":{"bibtex":"@article{Aspar_Steinhoff_Schäpermeier_Kerschke_Trautmann_Grimme_2022, title={The objective that freed me: a multi-objective local search approach for continuous single-objective optimization}, volume={1}, DOI={<a href=\"https://doi.org/10.1007/s11047-022-09919-w\">10.1007/s11047-022-09919-w</a>}, journal={Natural Computing}, author={Aspar, Pelin and Steinhoff, Vera and Schäpermeier, Lennart and Kerschke, Pascal and Trautmann, Heike and Grimme, Christian}, year={2022}, pages={1–15} }","ama":"Aspar P, Steinhoff V, Schäpermeier L, Kerschke P, Trautmann H, Grimme C. The objective that freed me: a multi-objective local search approach for continuous single-objective optimization. <i>Natural Computing</i>. 2022;1:1–15. doi:<a href=\"https://doi.org/10.1007/s11047-022-09919-w\">10.1007/s11047-022-09919-w</a>","mla":"Aspar, Pelin, et al. “The Objective That Freed Me: A Multi-Objective Local Search Approach for Continuous Single-Objective Optimization.” <i>Natural Computing</i>, vol. 1, 2022, pp. 1–15, doi:<a href=\"https://doi.org/10.1007/s11047-022-09919-w\">10.1007/s11047-022-09919-w</a>.","chicago":"Aspar, Pelin, Vera Steinhoff, Lennart Schäpermeier, Pascal Kerschke, Heike Trautmann, and Christian Grimme. “The Objective That Freed Me: A Multi-Objective Local Search Approach for Continuous Single-Objective Optimization.” <i>Natural Computing</i> 1 (2022): 1–15. <a href=\"https://doi.org/10.1007/s11047-022-09919-w\">https://doi.org/10.1007/s11047-022-09919-w</a>.","short":"P. Aspar, V. Steinhoff, L. Schäpermeier, P. Kerschke, H. Trautmann, C. Grimme, Natural Computing 1 (2022) 1–15.","ieee":"P. Aspar, V. Steinhoff, L. Schäpermeier, P. Kerschke, H. Trautmann, and C. Grimme, “The objective that freed me: a multi-objective local search approach for continuous single-objective optimization,” <i>Natural Computing</i>, vol. 1, pp. 1–15, 2022, doi: <a href=\"https://doi.org/10.1007/s11047-022-09919-w\">10.1007/s11047-022-09919-w</a>.","apa":"Aspar, P., Steinhoff, V., Schäpermeier, L., Kerschke, P., Trautmann, H., &#38; Grimme, C. (2022). The objective that freed me: a multi-objective local search approach for continuous single-objective optimization. <i>Natural Computing</i>, <i>1</i>, 1–15. <a href=\"https://doi.org/10.1007/s11047-022-09919-w\">https://doi.org/10.1007/s11047-022-09919-w</a>"},"type":"journal_article","department":[{"_id":"34"},{"_id":"819"}],"date_created":"2023-08-04T07:16:40Z"},{"abstract":[{"lang":"eng","text":"Graph convolutional networks (GCNs) are a powerful architecture for representation learning on documents that naturally occur as graphs, e.g., citation or social networks. However, sensitive personal information, such as documents with people{’}s profiles or relationships as edges, are prone to privacy leaks, as the trained model might reveal the original input. Although differential privacy (DP) offers a well-founded privacy-preserving framework, GCNs pose theoretical and practical challenges due to their training specifics. We address these challenges by adapting differentially-private gradient-based training to GCNs and conduct experiments using two optimizers on five NLP datasets in two languages. We propose a simple yet efficient method based on random graph splits that not only improves the baseline privacy bounds by a factor of 2.7 while retaining competitive F1 scores, but also provides strong privacy guarantees of epsilon = 1.0. We show that, under certain modeling choices, privacy-preserving GCNs perform up to 90{%} of their non-private variants, while formally guaranteeing strong privacy measures."}],"publication":"Proceedings of the Thirteenth Language Resources and Evaluation Conference","citation":{"short":"T. Igamberdiev, I. Habernal, in: Proceedings of the Thirteenth Language Resources and Evaluation Conference, European Language Resources Association, Marseille, France, 2022, pp. 338–350.","chicago":"Igamberdiev, Timour, and Ivan Habernal. “Privacy-Preserving Graph Convolutional Networks for Text Classification.” In <i>Proceedings of the Thirteenth Language Resources and Evaluation Conference</i>, 338–350. Marseille, France: European Language Resources Association, 2022.","apa":"Igamberdiev, T., &#38; Habernal, I. (2022). Privacy-Preserving Graph Convolutional Networks for Text Classification. <i>Proceedings of the Thirteenth Language Resources and Evaluation Conference</i>, 338–350.","ieee":"T. Igamberdiev and I. Habernal, “Privacy-Preserving Graph Convolutional Networks for Text Classification,” in <i>Proceedings of the Thirteenth Language Resources and Evaluation Conference</i>, 2022, pp. 338–350.","ama":"Igamberdiev T, Habernal I. Privacy-Preserving Graph Convolutional Networks for Text Classification. In: <i>Proceedings of the Thirteenth Language Resources and Evaluation Conference</i>. European Language Resources Association; 2022:338–350.","bibtex":"@inproceedings{Igamberdiev_Habernal_2022, place={Marseille, France}, title={Privacy-Preserving Graph Convolutional Networks for Text Classification}, booktitle={Proceedings of the Thirteenth Language Resources and Evaluation Conference}, publisher={European Language Resources Association}, author={Igamberdiev, Timour and Habernal, Ivan}, year={2022}, pages={338–350} }","mla":"Igamberdiev, Timour, and Ivan Habernal. “Privacy-Preserving Graph Convolutional Networks for Text Classification.” <i>Proceedings of the Thirteenth Language Resources and Evaluation Conference</i>, European Language Resources Association, 2022, pp. 338–350."},"type":"conference","department":[{"_id":"34"},{"_id":"820"}],"date_created":"2023-10-19T08:26:58Z","place":"Marseille, France","date_updated":"2023-10-19T12:05:12Z","year":"2022","title":"Privacy-Preserving Graph Convolutional Networks for Text Classification","status":"public","author":[{"first_name":"Timour","last_name":"Igamberdiev","full_name":"Igamberdiev, Timour"},{"full_name":"Habernal, Ivan","last_name":"Habernal","first_name":"Ivan","id":"101881"}],"user_id":"15504","page":"338–350","_id":"48299","publisher":"European Language Resources Association","language":[{"iso":"eng"}]},{"department":[{"_id":"34"},{"_id":"820"}],"type":"conference","place":"Gyeongju, Republic of Korea","date_created":"2023-10-19T08:27:05Z","abstract":[{"lang":"eng","text":"Text rewriting with differential privacy (DP) provides concrete theoretical guarantees for protecting the privacy of individuals in textual documents. In practice, existing systems may lack the means to validate their privacy-preserving claims, leading to problems of transparency and reproducibility. We introduce DP-Rewrite, an open-source framework for differentially private text rewriting which aims to solve these problems by being modular, extensible, and highly customizable. Our system incorporates a variety of downstream datasets, models, pre-training procedures, and evaluation metrics to provide a flexible way to lead and validate private text rewriting research. To demonstrate our software in practice, we provide a set of experiments as a case study on the ADePT DP text rewriting system, detecting a privacy leak in its pre-training approach. Our system is publicly available, and we hope that it will help the community to make DP text rewriting research more accessible and transparent."}],"citation":{"ieee":"T. Igamberdiev, T. Arnold, and I. Habernal, “DP-Rewrite: Towards Reproducibility and Transparency in Differentially Private Text Rewriting,” in <i>Proceedings of the 29th International Conference on Computational Linguistics</i>, 2022, pp. 2927–2933.","apa":"Igamberdiev, T., Arnold, T., &#38; Habernal, I. (2022). DP-Rewrite: Towards Reproducibility and Transparency in Differentially Private Text Rewriting. <i>Proceedings of the 29th International Conference on Computational Linguistics</i>, 2927–2933.","chicago":"Igamberdiev, Timour, Thomas Arnold, and Ivan Habernal. “DP-Rewrite: Towards Reproducibility and Transparency in Differentially Private Text Rewriting.” In <i>Proceedings of the 29th International Conference on Computational Linguistics</i>, 2927–2933. Gyeongju, Republic of Korea: International Committee on Computational Linguistics, 2022.","short":"T. Igamberdiev, T. Arnold, I. Habernal, in: Proceedings of the 29th International Conference on Computational Linguistics, International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 2022, pp. 2927–2933.","mla":"Igamberdiev, Timour, et al. “DP-Rewrite: Towards Reproducibility and Transparency in Differentially Private Text Rewriting.” <i>Proceedings of the 29th International Conference on Computational Linguistics</i>, International Committee on Computational Linguistics, 2022, pp. 2927–2933.","bibtex":"@inproceedings{Igamberdiev_Arnold_Habernal_2022, place={Gyeongju, Republic of Korea}, title={DP-Rewrite: Towards Reproducibility and Transparency in Differentially Private Text Rewriting}, booktitle={Proceedings of the 29th International Conference on Computational Linguistics}, publisher={International Committee on Computational Linguistics}, author={Igamberdiev, Timour and Arnold, Thomas and Habernal, Ivan}, year={2022}, pages={2927–2933} }","ama":"Igamberdiev T, Arnold T, Habernal I. DP-Rewrite: Towards Reproducibility and Transparency in Differentially Private Text Rewriting. In: <i>Proceedings of the 29th International Conference on Computational Linguistics</i>. International Committee on Computational Linguistics; 2022:2927–2933."},"publication":"Proceedings of the 29th International Conference on Computational Linguistics","user_id":"15504","_id":"48300","publisher":"International Committee on Computational Linguistics","language":[{"iso":"eng"}],"page":"2927–2933","date_updated":"2023-10-19T12:04:57Z","author":[{"last_name":"Igamberdiev","first_name":"Timour","full_name":"Igamberdiev, Timour"},{"full_name":"Arnold, Thomas","last_name":"Arnold","first_name":"Thomas"},{"first_name":"Ivan","last_name":"Habernal","full_name":"Habernal, Ivan","id":"101881"}],"title":"DP-Rewrite: Towards Reproducibility and Transparency in Differentially Private Text Rewriting","year":"2022","status":"public"},{"citation":{"ama":"Habernal I. How reparametrization trick broke differentially-private text representation learning. In: <i>Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)</i>. Association for Computational Linguistics; 2022. doi:<a href=\"https://doi.org/10.18653/v1/2022.acl-short.87\">10.18653/v1/2022.acl-short.87</a>","bibtex":"@inproceedings{Habernal_2022, title={How reparametrization trick broke differentially-private text representation learning}, DOI={<a href=\"https://doi.org/10.18653/v1/2022.acl-short.87\">10.18653/v1/2022.acl-short.87</a>}, booktitle={Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)}, publisher={Association for Computational Linguistics}, author={Habernal, Ivan}, year={2022} }","mla":"Habernal, Ivan. “How Reparametrization Trick Broke Differentially-Private Text Representation Learning.” <i>Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)</i>, Association for Computational Linguistics, 2022, doi:<a href=\"https://doi.org/10.18653/v1/2022.acl-short.87\">10.18653/v1/2022.acl-short.87</a>.","chicago":"Habernal, Ivan. “How Reparametrization Trick Broke Differentially-Private Text Representation Learning.” In <i>Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)</i>. 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