<div dir="ltr"><div class="gmail_default" style="font-size:small"><span id="gmail-docs-internal-guid-f9f3fae3-7fff-e999-fc97-52a78de495bd"><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="font-size:12pt;font-family:Arial,sans-serif;color:rgb(0,0,0);background-color:transparent;font-weight:700;font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;vertical-align:baseline">Call for Papers: Workshop on Social Choice and Learning Algorithms at AAMAS 2024</span></p><br><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="font-size:11pt;font-family:Arial,sans-serif;color:rgb(0,0,0);background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;vertical-align:baseline">We are delighted to announce that the 1st Workshop on Social Choice and Learning Algorithms (SCaLA-24) will take place at AAMAS 2024 in Auckland, New Zealand, May 6 or 7, 2024. It will feature technical sessions, a keynote speaker, and opportunities to develop collaborations between researchers working in social choice and those working in machine learning.</span></p><br><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="font-size:11pt;font-family:Arial,sans-serif;color:rgb(0,0,0);background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;vertical-align:baseline">The website and submission instructions can be found at the following link: <a href="https://sites.google.com/view/scala24">https://sites.google.com/view/scala24</a></span></p><br><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="font-size:11pt;font-family:Arial,sans-serif;color:rgb(0,0,0);background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;vertical-align:baseline">The submission deadline is Feb 5, 2024. We encourage submissions of fully developed research projects as well as preliminary explorations of novel ideas. Submissions should include components from both fields of social choice and machine learning (or closely related topics).</span></p><br><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="font-size:11pt;font-family:Arial,sans-serif;color:rgb(0,0,0);background-color:transparent;font-weight:700;font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;vertical-align:baseline">Topics of interest include:</span></p><ul style="margin-top:0px;margin-bottom:0px"><li dir="ltr" style="list-style-type:disc;font-size:11pt;font-family:Arial,sans-serif;color:rgb(0,0,0);background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;vertical-align:baseline;white-space:pre"><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt" role="presentation"><span style="font-size:11pt;background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;vertical-align:baseline">Computational social choice</span></p></li><li dir="ltr" style="list-style-type:disc;font-size:11pt;font-family:Arial,sans-serif;color:rgb(0,0,0);background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;vertical-align:baseline;white-space:pre"><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt" role="presentation"><span style="font-size:11pt;background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;vertical-align:baseline">Fair Division</span></p></li><li dir="ltr" style="list-style-type:disc;font-size:11pt;font-family:Arial,sans-serif;color:rgb(0,0,0);background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;vertical-align:baseline;white-space:pre"><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt" role="presentation"><span style="font-size:11pt;background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;vertical-align:baseline">Matching</span></p></li><li dir="ltr" style="list-style-type:disc;font-size:11pt;font-family:Arial,sans-serif;color:rgb(0,0,0);background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;vertical-align:baseline;white-space:pre"><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt" role="presentation"><span style="font-size:11pt;background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;vertical-align:baseline">Voting theory</span></p></li><li dir="ltr" style="list-style-type:disc;font-size:11pt;font-family:Arial,sans-serif;color:rgb(0,0,0);background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;vertical-align:baseline;white-space:pre"><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt" role="presentation"><span style="font-size:11pt;background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;vertical-align:baseline">Sortition</span></p></li><li dir="ltr" style="list-style-type:disc;font-size:11pt;font-family:Arial,sans-serif;color:rgb(0,0,0);background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;vertical-align:baseline;white-space:pre"><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt" role="presentation"><span style="font-size:11pt;background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;vertical-align:baseline">Clustering</span></p></li><li dir="ltr" style="list-style-type:disc;font-size:11pt;font-family:Arial,sans-serif;color:rgb(0,0,0);background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;vertical-align:baseline;white-space:pre"><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt" role="presentation"><span style="font-size:11pt;background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;vertical-align:baseline">Ensemble learning</span></p></li><li dir="ltr" style="list-style-type:disc;font-size:11pt;font-family:Arial,sans-serif;color:rgb(0,0,0);background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;vertical-align:baseline;white-space:pre"><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt" role="presentation"><span style="font-size:11pt;background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;vertical-align:baseline">Explainable ML</span></p></li><li dir="ltr" style="list-style-type:disc;font-size:11pt;font-family:Arial,sans-serif;color:rgb(0,0,0);background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;vertical-align:baseline;white-space:pre"><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt" role="presentation"><span style="font-size:11pt;background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;vertical-align:baseline">Language models</span></p></li><li dir="ltr" style="list-style-type:disc;font-size:11pt;font-family:Arial,sans-serif;color:rgb(0,0,0);background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;vertical-align:baseline;white-space:pre"><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt" role="presentation"><span style="font-size:11pt;background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;vertical-align:baseline">Learning preferences</span></p></li><li dir="ltr" style="list-style-type:disc;font-size:11pt;font-family:Arial,sans-serif;color:rgb(0,0,0);background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;vertical-align:baseline;white-space:pre"><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt" role="presentation"><span style="font-size:11pt;background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;vertical-align:baseline">PAC-learning</span></p></li></ul><br><br><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="font-size:11pt;font-family:Arial,sans-serif;color:rgb(0,0,0);background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;vertical-align:baseline">Examples of interesting connections between these topics include, but are not at all limited to:</span></p><ul style="margin-top:0px;margin-bottom:0px"><li dir="ltr" style="list-style-type:disc;font-size:11pt;font-family:Arial,sans-serif;color:rgb(0,0,0);background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;vertical-align:baseline;white-space:pre"><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt" role="presentation"><span style="font-size:11pt;background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;vertical-align:baseline">Using machine learning to learn new mechanisms for matching</span></p></li><li dir="ltr" style="list-style-type:disc;font-size:11pt;font-family:Arial,sans-serif;color:rgb(0,0,0);background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;vertical-align:baseline;white-space:pre"><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt" role="presentation"><span style="font-size:11pt;background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;vertical-align:baseline">Novel uses of social choice for ensemble learning</span></p></li><li dir="ltr" style="list-style-type:disc;font-size:11pt;font-family:Arial,sans-serif;color:rgb(0,0,0);background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;vertical-align:baseline;white-space:pre"><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt" role="presentation"><span style="font-size:11pt;background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;vertical-align:baseline">Exploring the application of fair division concepts to clustering problems, or vice-versa</span></p></li><li dir="ltr" style="list-style-type:disc;font-size:11pt;font-family:Arial,sans-serif;color:rgb(0,0,0);background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;vertical-align:baseline;white-space:pre"><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt" role="presentation"><span style="font-size:11pt;background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;vertical-align:baseline">Applying multi-winner voting concepts to multi-class classification tasks</span></p></li></ul><br><br><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="font-size:11pt;font-family:Arial,sans-serif;color:rgb(0,0,0);background-color:transparent;font-weight:700;font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;vertical-align:baseline">Organizing Committee</span></p><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="font-size:11pt;font-family:Arial,sans-serif;color:rgb(0,0,0);background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;vertical-align:baseline">Ben Armstrong</span></p><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="font-size:11pt;font-family:Arial,sans-serif;color:rgb(0,0,0);background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;vertical-align:baseline">Roy Fairstein</span></p><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="font-size:11pt;font-family:Arial,sans-serif;color:rgb(0,0,0);background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;vertical-align:baseline">Nick Mattei</span></p><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="font-size:11pt;font-family:Arial,sans-serif;color:rgb(0,0,0);background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;vertical-align:baseline">Zoi Terzopoulou</span></p></span><br class="gmail-Apple-interchange-newline"></div><div><br></div><span class="gmail_signature_prefix">-- </span><br><div dir="ltr" class="gmail_signature" data-smartmail="gmail_signature"><div dir="ltr"><div><div dir="ltr"><div><div><b>Nicholas Mattei</b></div><div><font size="1">Assistant Professor, Tulane University</font></div><div><font size="1"><a href="mailto:nsmattei@tulane.edu" target="_blank">nsmattei@tulane.edu</a> | <a href="http://www.nickmattei.net/" target="_blank">www.nickmattei.net</a></font></div><div><font size="1">Stanley Thomas Hall | 305B</font></div><div><font size="1">+1 504 865 5782</font></div><div><font size="1">Department of Computer Science</font></div><div><font size="1">Tulane University</font></div><div><font size="1">6823 St Charles Ave</font></div><div><font size="1">New Orleans, LA 70118</font></div></div><div><br></div></div></div></div></div></div>