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<!DOCTYPE html> <html lang="en" class="no-js"> <head> <meta charset="utf-8"> <meta http-equiv="X-UA-Compatible" content="IE=edge,chrome=1"> <link rel="icon" href="/static/img/favicon.ico" /> <link rel="apple-touch-icon" href="/static/img/apple-touch-icon.png"> <title>Scholarship :: FAT ML</title> <meta name="viewport" content="width=device-width, initial-scale=1.0"> <link href="https://fonts.googleapis.com/css?family=Open+Sans:400,400i,700|Roboto+Slab:400,700" rel="stylesheet"> <link href="/static/sass/main.css" rel="stylesheet" type="text/css" />  <script> (function(H){ H.className = H.className.replace(/\bno-js\b/,'js') })(document.documentElement); </script> </head> <body class="standard-page"> <div class="site-bg"> <nav class="site-header navbar navbar-default"> <div class="container"> <div class="navbar-header"> <button type="button" class="navbar-toggle collapsed" data-toggle="collapse" data-target="#site-header-nav" aria-expanded="false"> <span class="sr-only">Toggle navigation</span> <span class="icon-bar"></span> <span class="icon-bar"></span> <span class="icon-bar"></span> </button> <a class="navbar-brand" href="/"> <img src="/static/img/fatml-header-logo.png" srcset="/static/img/fatml-header-logo.svg 1x" alt="FAT ML 2016" height="20" width="90"> </a> </div>  <div class="collapse navbar-collapse" id="site-header-nav"> <ul class="nav navbar-nav" role="navigation"> <li ><a href="/schedule/2018">2018</a></li> <li ><a href="/schedule/2017">2017</a></li> <li ><a href="/schedule/2016">2016</a></li> <li ><a href="/schedule/2015">2015</a></li> <li ><a href="/schedule/2014">2014</a></li> <li ><a href="/organization">Organization</a></li> <li class="active"><a href="/resources/relevant-scholarship">Resources</a></li> <li><a href="https://lists.princeton.edu/cgi-bin/wa?SUBED1=fatml&A=1">Mailing list</a></li> </ul> <ul class="nav navbar-nav navbar-right">  </ul> </div> </nav> <nav class="workshop-navbar navbar navbar-inverse"> <div class="container"> <div class="navbar-header"> <button type="button" class="navbar-toggle collapsed" data-toggle="collapse" data-target="#workshop-header-nav" aria-expanded="false"> <span class="sr-only">Toggle navigation</span> <span class="icon-bar"></span> <span class="icon-bar"></span> <span class="icon-bar"></span> </button> <a class="navbar-brand" href="/resources">Resources</a> </div> <div class="collapse navbar-collapse" id="workshop-header-nav"> <ul class="nav navbar-nav" role="navigation"> <li><a href="/resources/relevant-scholarship">Scholarship</a></li> <li><a href="/resources/relevant-events">Events</a></li> <li><a href="/resources/relevant-projects">Projects</a></li> <li><a href="/resources/principles-and-best-practices">Principles and Best Practices</a></li> </ul> </div> </div> </nav> <div class="general-content"> <div class="container"> <div class="general-content__page"> <h1>Scholarship</h1> <div class="row"> <div class="standard-layout__primary-column"> <ul> <li>Barreno, Marco, Blaine Nelson, Anthony D Joseph, and J D Tygar. “The Security of Machine Learning.” Machine Learning 81, no. 2 (May 20, 2010): 121–48. <a href="http://doi.org/10.1007/s10994-010-5188-5">doi:10.1007/s10994-010-5188-5</a></li> <li>Berendt, Bettina, and Soren Preibusch. “Better Decision Support Through Exploratory Discrimination-Aware Data Mining: Foundations and Empirical Evidence.” Artificial Intelligence and Law 22, no. 2 (January 10, 2014): 175–209. <a href="http://doi.org/10.1007/s10506-013-9152-0">doi:10.1007/s10506-013-9152-0</a></li> <li>Berendt, Bettina, and Soren Preibusch. “Exploring Discrimination: a User-Centric Evaluation of Discrimination-Aware Data Mining.” 2012 IEEE 12th International Conference on Data Mining Workshops (December 10, 2012): 344–351. <a href="http://doi.org/10.1109/ICDMW.2012.109">doi:10.1109/ICDMW.2012.109</a></li> <li>Calders, Toon, and Sicco Verwer. “Three Naive Bayes Approaches for Discrimination-Free Classification.” Data Mining and Knowledge Discovery 21, no. 2 (July 27, 2010): 277–292. <a href="http://doi.org/10.1007/s10618-010-0190-x">doi:10.1007/s10618-010-0190-x</a></li> <li>Calders, Toon, Faisal Kamiran, and Mykola Pechenizkiy. “Building Classifiers with Independency Constraints.” 2009 IEEE 9th International Conference on Data Mining Workshops (December 6, 2009): 13–18. <a href="http://doi.org/10.1109/ICDMW.2009.83">doi:10.1109/ICDMW.2009.83</a></li> <li>Custers, Bart, and Bart Schermer. "Responsibly Innovating Data Mining and Profiling Tools: A New Approach to Discrimination Sensitive and Privacy Sensitive Attributes." Responsible Innovation 1: Innovative Solutions for Global Issues. (2014): 335-350. <a href="http://doi.org/10.1007/978-94-017-8956-1_19">doi:10.1007/978-94-017-8956-1_19</a></li> <li>Custers, Bart, Toon Calders, Bart Schermer, and Tal Z Zarsky. Discrimination and Privacy in the Information Society: Data Mining and Profiling in Large Databases. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. <a href="http://doi.org/10.1007/978-3-642-30487-3">doi:10.1007/978-3-642-30487-3</a></li> <li>Datta, Anupam, Shayak Sen, and Yair Zick. Algorithmic Transparency via Quantitative Input Influence: Theory and Experiments with Learning Systems, Proceedings of 37th IEEE Symposium on Security and Privacy (May 2016). <a href="https://www.andrew.cmu.edu/user/danupam/datta-sen-zick-oakland16.pdf">https://www.andrew.cmu.edu/user/danupam/datta-sen-zick-oakland16.pdf</a></li> <li>DeDeo, Simon. "Wrong Side of the Tracks: Big Data and Protected Categories" (May 27, 2015). <a href="http://arxiv.org/abs/1412.4643">arXiv:1412.4643v2</a></li> <li>Dwork, Cynthia, Moritz Hardt, Toniann Pitassi, Omer Reingold, and Richard Zemel. “Fairness Through Awareness,” 2012 Proceedings of the 3rd Innovations in Theoretical Computer Science Conference (January 9, 2012): 214–226. <a href="http://doi.org/10.1145/2090236.2090255">doi:10.1145/2090236.2090255</a></li> <li>El-Arini, Khalid, Ulrich Paquet, Ralf Herbrich, Jurgen Van Gael, and Blaise Agüera y Arcas. “Transparent User Models for Personalization,” 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. (August 8, 2012): 678-686. <a href="http://doi.org/10.1145/2339530.2339639">doi:10.1145/2339530.2339639</a></li> <li>Feldman, Michael, Sorelle Friedler, John Moeller, Carlos Scheidegger, and Suresh Venkatasubramanian. "Certifying and Removing Disparate Impact" (July 16, 2015). <a href="http://arxiv.org/abs/1412.3756">arXiv:1412.3756v3</a></li> <li>Freitas, Alex A. “Comprehensible Classification Models - A Position Paper.” ACM SIGKDD Explorations Newsletter 15, no. 1 (March 17, 2014): 1–10. <a href="http://doi.org/10.1145/2594473.2594475">doi:10.1145/2594473.2594475</a></li> <li>Hajian, Sara, and Josep Domingo-Ferrer. “A Methodology for Direct and Indirect Discrimination Prevention in Data Mining.” IEEE Transactions on Knowledge and Data Engineering 25, no. 7 (May 21, 2013): 1445–1459. <a href="http://doi.org/10.1109/TKDE.2012.72">doi:10.1109/TKDE.2012.72</a></li> <li>Hajian, Sara, and Josep Domingo-Ferrer. “A Study on the Impact of Data Anonymization on Anti-Discrimination.” 2012 IEEE 12th International Conference on Data Mining Workshops (December 10, 2012): 352–359. <a href="http://doi.org/10.1109/ICDMW.2012.19">doi:10.1109/ICDMW.2012.19</a></li> <li>Hajian, Sara, Josep Domingo-Ferrer, Anna Monreale, Dino Pedreschi, and Fosca Giannotti. "Discrimination- and Privacy-Aware Patterns." Data Mining and Knowledge Discovery. Forthcoming. <a href="http://doi.org/10.1007/s10618-014-0393-7">doi:10.1007/s10618-014-0393-7</a></li> <li>Hajian, Sara, Anna Monreale, Dino Pedreschi, Josep Domingo-Ferrer, and Fosca Giannotti. “Fair Pattern Discovery.” 2014 Proceedings of the 29th Annual ACM Symposium on Applied Computing (March 24, 2014): 113-120 <a href="http://doi.org/10.1145/2554850.2555043">doi:10.1145/2554850.2555043</a></li> <li>Hajian, Sara, Anna Monreale, Dino Pedreschi, Josep Domingo-Ferrer, and Fosca Giannotti. “Injecting Discrimination and Privacy Awareness Into Pattern Discovery.” 2012 IEEE 12th International Conference on Data Mining Workshops (December 10, 2012): 360–369, <a href="http://doi.org/10.1109/ICDMW.2012.51">doi:10.1109/ICDMW.2012.51</a></li> <li>Hajian, Sara, Josep Domingo-Ferrer, and Antoni Martinez-Balleste. “Discrimination Prevention in Data Mining for Intrusion and Crime Detection.” 2011 IEEE Symposium on Computational Intelligence in Cyber Security (April 11-15, 2011): 47–54. <a href="http://doi.org/10.1109/CICYBS.2011.5949405">doi:10.1109/CICYBS.2011.5949405</a></li> <li>Hajian, Sara, Josep Domingo-Ferrer, and Oriol Farràs. “Generalization-Based Privacy Preservation and Discrimination Prevention in Data Publishing and Mining.” Data Mining and Knowledge Discovery 28, no. 5-6 (January 25, 2014): 1158-1188. <a href="http://doi.org/10.1007/s10618-014-0346-1">doi:10.1007/s10618-014-0346-1</a></li> <li>Hajian, Sara. “Simultaneous Discrimination Prevention and Privacy Protection in Data Publishing and Mining.” PhD Thesis. Universitat Rovira i Virgili. (June 28, 2013). <a href="http://arxiv.org/abs/1306.6805">arXiv:1306.6805</a></li> <li>Herlocker, Jonathan L, Joseph A Konstan, and John Riedl. “Explaining Collaborative Filtering Recommendations,” Proceedings of the 2000 ACM Conference on Computer Supported Cooperative Work. (December 1, 2000): 241-250. <a href="http://doi.org/10.1145/358916.358995">doi:10.1145/358916.358995.</a></li> <li>Kamiran, Faisal, and Toon Calders. “Classifying Without Discriminating.” 2009 2nd International Conference on Computer, Control and Communication. (17-18, February 2009): 1–6. <a href="http://doi.org/10.1109/IC4.2009.4909197">doi:10.1109/IC4.2009.4909197</a></li> <li>Kamiran, Faisal, and Toon Calders. “Data Preprocessing Techniques for Classification Without Discrimination.” Knowledge and Information Systems 33, no. 1 (December 3, 2011): 1–33. <a href="http://doi.org/10.1007/s10115-011-0463-8">doi:10.1007/s10115-011-0463-8</a></li> <li>Kamiran, Faisal, Asim Karim, Sicco Verwer, and Heike Goudriaan. “Classifying Socially Sensitive Data Without Discrimination: an Analysis of a Crime Suspect Dataset.” 2012 IEEE 12th International Conference on Data Mining Workshops (December 10, 2012): 370–377. <a href="http://doi.org/10.1109/ICDMW.2012.117">doi:10.1109/ICDMW.2012.117</a></li> <li>Kamiran, Faisal, Indrė Žliobaitė, and Toon Calders. “Quantifying Explainable Discrimination and Removing Illegal Discrimination in Automated Decision Making.” Knowledge and Information Systems 35, no. 3 (November 18, 2012): 613–44. <a href="http://doi.org/10.1007/s10115-012-0584-8">doi:10.1007/s10115-012-0584-8</a></li> <li>Kamiran, Faisal, Toon Calders, and Mykola Pechenizkiy. “Discrimination Aware Decision Tree Learning.” 2010 IEEE 10th International Conference on Data Mining (December 13-17, 2010): 869–874. <a href="http://doi.org/10.1109/ICDM.2010.50">doi:10.1109/ICDM.2010.50</a></li> <li>Kamishima, Toshihiro, Shotaro Akaho, and Jun Sakuma. “Fairness-Aware Learning Through Regularization Approach.” 2011 IEEE 11th International Conference on Data Mining Workshops (December 11, 2011): 643–650. <a href="http://doi.org/10.1109/ICDMW.2011.83">doi:10.1109/ICDMW.2011.83</a></li> <li>Kamishima, Toshihiro, Shotaro Akaho, Hideki Asoh, and Jun Sakuma. “Considerations on Fairness-Aware Data Mining." 2012 IEEE 12th International Conference on Data Mining Workshops. (December 10, 2012): 378–385. <a href="http://doi.org/10.1109/ICDMW.2012.101">doi:10.1109/ICDMW.2012.101</a></li> <li>Kamishima, Toshihiro, Shotaro Akaho, Hideki Asoh, and Jun Sakuma. “Fairness-Aware Classifier with Prejudice Remover Regularizer.” 2012 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. (September 24-28, 2012): 35–50. <a href="http://doi.org/10.1007/978-3-642-33486-3_3">doi:10.1007/978-3-642-33486-3_3</a></li> <li>Kamishima, Toshihiro, Shotaro Akaho, Hideki Asoh, and Jun Sakuma. “The Independence of Fairness-Aware Classifiers." 2013 IEEE 13th International Conference on Data Mining Workshops. (December 7-10, 2013): 849–58. <a href="http://doi.org/10.1109/ICDMW.2013.133">doi:10.1109/ICDMW.2013.133</a></li> <li>Letham, Benjamin, Cynthia Rudin, Tyler McCormick and David Madigan. "Building Interpretable Classifiers with Rules using Bayesian Analysis: Building a Better Stroke Prediction Model." (August 2013). <a href="http://web.mit.edu/rudin/www/LethamRuMcMa14.pdf">http://web.mit.edu/rudin/www/LethamRuMcMa14.pdf</a></li> <li>Lowd, Daniel, and Christopher Meek. “Adversarial Learning,” 11th ACM SIGKDD International Conference on Knowledge Discovery in Data Mining. (August 21, 2005): 641-647. <a href="http://doi.org/10.1145/1081870.1081950">doi:10.1145/1081870.1081950</a></li> <li>Luong, Binh Thanh, Salvatore Ruggieri, and Franco Turini. “K-NN as an Implementation of Situation Testing for Discrimination Discovery and Prevention.” 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. (July 21, 2011): 502–510. <a href="http://doi.org/10.1145/2020408.2020488">doi:10.1145/2020408.2020488</a></li> <li>Mancuhan, Koray, and Chris Clifton. “Combating Discrimination Using Bayesian Networks.” Artificial Intelligence and Law 22, no. 2 (February 17, 2014): 211–238. <a href="http://doi.org/10.1007/s10506-014-9156-4">doi:10.1007/s10506-014-9156-4</a></li> <li>Mancuhan, Koray, and Chris Clifton. “Discriminatory Decision Policy Aware Classification." 2012 IEEE 12th International Conference on Data Mining Workshops. (December 10, 2012): 386–393. <a href="http://doi.org/10.1109/ICDMW.2012.96">doi:10.1109/ICDMW.2012.96</a></li> <li>Martens, David, and Bart Baesens, “Building Acceptable Classification Models.” Annals of Information Systems 8 (2010): 53-74. <a href="http://doi.org/10.1007/978-1-4419-1280-0_3">doi:10.1007/978-1-4419-1280-0_3</a></li> <li>Martens, David, and Foster Provost, “Explaining Data-Driven Document Classifications,” MIS Quarterly 38, no. 1 (March 2014): 73–99. <a href=" http://misq.org/explaining-data-driven-document-classifications.html">http://misq.org/explaining-data-driven-document-classifications.html</a></li> <li>Martens, David, Jan Vanthienen, Wouter Verbeke, and Bart Baesens. "Performance of Classification Models from a User Perspective." Decision Support Systems 51, no. 4 (November 2011): 782–793. <a href="http://doi.org/doi:10.1016/j.dss.2011.01.013">doi:10.1016/j.dss.2011.01.01</a></li> <li>Mascetti, Sergio, Annarita Ricci, and Salvatore Ruggieri. “Introduction to Special Issue on Computational Methods for Enforcing Privacy and Fairness in the Knowledge Society.” Artificial Intelligence and Law 22, no. 2 (February 11, 2014): 109–11. <a href="http://doi.org/10.1007/s10506-014-9153-7">doi:10.1007/s10506-014-9153-7</a></li> <li>Moritz Hardt, A Study of Privacy and Fairness in Sensitive Data Analysis, PhD Thesis, Princeton University (2011) <a href="http://arks.princeton.edu/ark:/88435/dsp01vq27zn422">http://arks.princeton.edu/ark:/88435/dsp01vq27zn422</a></li> <li>Pedreschi, Dino, Salvatore Ruggieri, and Franco Turini. “A Study of Top-K Measures for Discrimination Discovery.” 2012 Proceedings of the 27th Annual ACM Symposium on Applied Computing. (March 26, 2012) 126–131. <a href="http://doi.org/10.1145/2245276.2245303">doi:10.1145/2245276.2245303</a></li> <li>Pedreschi, Dino, Salvatore Ruggieri, and Franco Turini. “Measuring Discrimination in Socially-Sensitive Decision Records.” Proceedings of the 2009 SIAM International Conference on Data Mining. (2009): 581-592. <a href="http://doi.org/10.1137/1.9781611972795.50">doi:10.1137/1.9781611972795.50</a></li> <li>Pedreschi, Dino, Salvatore Ruggieri, and Franco Turini. “Discrimination-Aware Data Mining.” 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. (July 24, 2008): 560-568. <a href="http://doi.org/10.1145/1401890.1401959">doi:10.1145/1401890.1401959</a></li> <li>Pope, Devin G, and Justin R Sydnor. “Implementing Anti-Discrimination Policies in Statistical Profiling Models.” American Economic Journal: Economic Policy 3, no. 3 (August 2011): 206–31. <a href="http://doi.org/10.1257/pol.3.3.206">doi:10.1257/pol.3.3.206</a></li> <li>Romei, Andrea, and Salvatore Ruggieri. “A Multidisciplinary Survey on Discrimination Analysis.” The Knowledge Engineering Review 29, no. 5 (April 3, 2013): 1–57. <a href="http://doi.org/10.1017/S0269888913000039">doi:10.1017/S0269888913000039</a></li> <li>Romei, Andrea, Salvatore Ruggieri, and Franco Turini. “Discovering Gender Discrimination in Project Funding." 2012 IEEE 12th International Conference on Data Mining Workshops. (December 10, 2012): 394–401. <a href="http://doi.org/10.1109/ICDMW.2012.39">doi:10.1109/ICDMW.2012.39</a></li> <li>Romei, Andrea, Salvatore Ruggieri, and Franco Turini. “Discrimination Discovery in Scientific Project Evaluation: A Case Study.” Expert Systems with Applications 40, no. 15 (November 2013): 6064–79. <a href="http://doi.org/10.1016/j.eswa.2013.05.016">doi:10.1016/j.eswa.2013.05.016</a></li> <li>Ruggieri, Salvatore, Dino Pedreschi, and Franco Turini. “Data Mining for Discrimination Discovery.” ACM Transactions on Knowledge Discovery From Data 4, no. 2 (May 1, 2010): 1–40. <a href="http://doi.org/10.1145/1754428.1754432">doi:10.1145/1754428.1754432</a></li> <li>Ruggieri, Salvatore, Dino Pedreschi, and Franco Turini. “DCUBE: Discrimination Discovery in Databases." Proceedings of the 2010 ACM SIGMOD International Conference on Management of Data (June 6, 2010): 1127–1130. <a href="http://doi.org/10.1145/1807167.1807298">doi:10.1145/1807167.1807298</a></li> <li>Ruggieri, Salvatore, Dino Pedreschi, and Franco Turini. “Integrating Induction and Deduction for Finding Evidence of Discrimination.” Artificial Intelligence and Law 18, no. 1 (June 5, 2010): 1–43. <a href="http://doi.org/10.1007/s10506-010-9089-5">doi:10.1007/s10506-010-9089-5</a></li> <li>Ruggieri, Salvatore, Hajian, Sara, Faisal Kamiran, and Xiangliang Zhang. “Anti-discrimination Analysis Using Privacy Attack Strategies.” 2014 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (2014): 694-710. <a href="http://doi.org/10.1007/978-3-662-44851-9_44">doi:10.1007/978-3-662-44851-9_44</a></li> <li>Ruggieri, Salvatore. “Data Anonymity Meets Non-Discrimination.” 2013 IEEE 13th International Conference on Data Mining Workshops (December 7-10, 2013): 875–882. <a href="http://doi.org/10.1109/ICDMW.2013.56">doi:10.1109/ICDMW.2013.56</a></li> <li>Sinha, Rashmi, and Kirsten Swearingen. “The Role of Transparency in Recommender Systems.” CHI '02 Extended Abstracts on Human Factors in Computing Systems. (April 20, 2002): 830-831. <a href="http://doi.org/10.1145/506443.506619">doi:10.1145/506443.506619.</a></li> <li>Ustun, Berk, and Cynthia Rudin. "Methods and Models for Interpretable Linear Classification" (October 1, 2014). <a href="http://arxiv.org/abs/1405.4047">arXiv:1405.4047</a></li> <li>Zemel, Rich, Yu Wu, Kevin Swersky, Toni Pitassi, and Cynthia Dwork. “Learning Fair Representations.” 30th International Conference on Machine Learning (June 16-21, 2013) <a href="http://jmlr.org/proceedings/papers/v28/zemel13.html">http://jmlr.org/proceedings/papers/v28/zemel13.html</a></li> <li>Žliobaitė, Indre, Faisal Kamiran, and Toon Calders. “Handling Conditional Discrimination." 2011 IEEE 11th International Conference on Data Mining. (December 11-14, 2011): 992–1001. <a href="http://doi.org/10.1109/ICDM.2011.72">doi:10.1109/ICDM.2011.72</a></li> </ul> </div> </div> </div> </div> </div> </div>  <script type="text/javascript" src="/static/javascripts/jquery.js" charset="utf-8"></script> <script type="text/javascript" src="/static/javascripts/bootstrap.js" charset="utf-8"></script> <script type="text/javascript" src="/static/javascripts/js.cookie.js" charset="utf-8"></script> <script type="text/javascript" src="/static/conference/javascripts/profile-photo.js" charset="utf-8"></script> </body> </html>