<div dir="ltr"><div><span id="gmail-docs-internal-guid-18654a40-7fff-848a-7e4a-c605b51ea5e4"><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:normal;vertical-align:baseline;white-space:pre-wrap">2nd Call for Papers and Deadline Extension: Workshop on Social Choice and Learning Algorithms at IJCAI 2026</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:normal;vertical-align:baseline;white-space:pre-wrap">We are delighted to announce that the 3rd Workshop on Social Choice and Learning Algorithms (SCaLA-26) will take place at IJCAI during August 2026 in Bremen, Germany. It will feature technical sessions, a keynote speaker, and opportunities to forge 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:normal;vertical-align:baseline;white-space:pre-wrap">The website and submission instructions can be found at the following link: </span><a href="https://sites.google.com/view/scala26" style="text-decoration:none"><span style="font-size:11pt;font-family:Arial,sans-serif;background-color:transparent;font-variant:normal;text-decoration:underline;vertical-align:baseline;white-space:pre-wrap">https://sites.google.com/view/scala26</span></a><span style="font-size:11pt;font-family:Arial,sans-serif;color:rgb(0,0,0);background-color:transparent;font-variant:normal;vertical-align:baseline;white-space:pre-wrap"> </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:normal;vertical-align:baseline;white-space:pre-wrap">The submission deadline is </span><span style="font-size:11pt;font-family:Arial,sans-serif;color:rgb(0,0,0);background-color:transparent;font-variant:normal;text-decoration:line-through;vertical-align:baseline;white-space:pre-wrap">May 8, 2026</span><span style="font-size:11pt;font-family:Arial,sans-serif;color:rgb(0,0,0);background-color:transparent;font-variant:normal;vertical-align:baseline;white-space:pre-wrap"> </span><span style="font-size:11pt;font-family:Arial,sans-serif;color:rgb(0,0,0);background-color:transparent;font-weight:700;font-variant:normal;vertical-align:baseline;white-space:pre-wrap">May 15th</span><span style="font-size:11pt;font-family:Arial,sans-serif;color:rgb(0,0,0);background-color:transparent;font-variant:normal;vertical-align:baseline;white-space:pre-wrap">. We encourage submissions of fully developed research projects, or extended abstracts representing 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:normal;vertical-align:baseline;white-space:pre-wrap">Topics of interest include (but not 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: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:normal;vertical-align:baseline;white-space:pre-wrap">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: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:normal;vertical-align:baseline;white-space:pre-wrap">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: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:normal;vertical-align:baseline;white-space:pre-wrap">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: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:normal;vertical-align:baseline;white-space:pre-wrap">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: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:normal;vertical-align:baseline;white-space:pre-wrap">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: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:normal;vertical-align:baseline;white-space:pre-wrap">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: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:normal;vertical-align:baseline;white-space:pre-wrap">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: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:normal;vertical-align:baseline;white-space:pre-wrap">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: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:normal;vertical-align:baseline;white-space:pre-wrap">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: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:normal;vertical-align:baseline;white-space:pre-wrap">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: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:normal;vertical-align:baseline;white-space:pre-wrap">PAC-learning</span></p></li></ul><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:normal;vertical-align:baseline;white-space:pre-wrap">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: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:normal;vertical-align:baseline;white-space:pre-wrap">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: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:normal;vertical-align:baseline;white-space:pre-wrap">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: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:normal;vertical-align:baseline;white-space:pre-wrap">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: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:normal;vertical-align:baseline;white-space:pre-wrap">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:normal;vertical-align:baseline;white-space:pre-wrap">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:normal;vertical-align:baseline;white-space:pre-wrap">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:normal;vertical-align:baseline;white-space:pre-wrap">Saar Cohen</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:normal;vertical-align:baseline;white-space:pre-wrap">Nicholas 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:normal;vertical-align:baseline;white-space:pre-wrap">Zoi Terzopoulou</span></p><br></span></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 dir="ltr"><div><div><b>Nicholas Mattei</b></div><div><font size="1">Associate Professor, Tulane University</font></div><div><font size="1">Co-Director, <a href="https://sse.tulane.edu/cs/ceai" target="_blank">Tulane Center For Community Engaged AI</a></font></div><div><span style="font-size:x-small">Co-Author, <a href="https://mitpress.mit.edu/9780262048064/computing-and-technology-ethics/" target="_blank">Computing and Technology Ethics: Engaging through Science Fiction </a></span></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">+1 504 247 1416</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>