<div dir="ltr"><p dir="ltr" style="line-height:1.656;margin-top:0pt;margin-bottom:0pt;text-align:left" id="gmail-docs-internal-guid-dcd664e9-7fff-f5e7-f4bd-90c90e3a3783"><span style="font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:700;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap"><span style="border:medium none;display:inline-block;overflow:hidden;width:135px;height:135px"><img src="https://lh5.googleusercontent.com/FyoR79ixoW2Ocl3VkcmAL7K7a65PEI3ypejoVSsLGGnBMMmDr_208y9SiH26Bju1Yl2la-eUXBVOBqayMgN492Laqy8rv5Bb2BD5eNkYQRZanE9VzVjDesykgAnJc1EVunEEPrdC" style="margin-left: 0px; margin-top: 0px;" width="135" height="135"></span></span></p><p dir="ltr" style="line-height:1.656;margin-top:0pt;margin-bottom:0pt;text-align:left"><span style="font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:700;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap">16th International Workshop on Mining and Learning with Graphs (MLG 2020)</span></p><p dir="ltr" style="line-height:1.656;margin-top:0pt;margin-bottom:0pt;text-align:left"><span style="font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap">August 24, 2020</span></p><p dir="ltr" style="line-height:1.656;margin-top:0pt;margin-bottom:0pt;text-align:left"><span style="font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap">In conjunction with KDD (Virtual Conference)</span></p><p dir="ltr" style="line-height:1.656;margin-top:0pt;margin-bottom:0pt;text-align:left"><a href="http://www.mlgworkshop.org/2018/" style="text-decoration:none"><span style="font-size:11pt;font-family:Arial;color:rgb(17,85,204);background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap">http://www.mlgworkshop.org/2020/</span></a></p><p dir="ltr" style="line-height:1.656;margin-top:0pt;margin-bottom:0pt;text-align:left"><span style="font-size:11pt;font-family:Arial;color:rgb(255,0,0);background-color:transparent;font-weight:700;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap">Submission Deadline:  June 15, 2020</span></p><div style="text-align:left"><br></div><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt;text-align:left"><span style="font-size:11pt;font-family:Arial;color:rgb(255,0,0);background-color:transparent;font-weight:700;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap">Due to public health concerns in light of the unfolding COVID-19 outbreak, we follow ACM SIGKDD and the KDD 2020 organizing committee guidelines and will hold MLG as a virtual workshop.  </span></p><div style="text-align:left"><br><br></div><p dir="ltr" style="line-height:1.656;margin-top:0pt;margin-bottom:0pt;text-align:left"><span style="font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:700;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap">Call for papers:</span></p><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:12pt;text-align:left"><span style="font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap">This workshop is a forum for exchanging ideas and methods for mining and learning with graphs, developing new common understandings of the problems at hand, sharing of data sets where applicable, and leveraging existing knowledge from different disciplines. The goal is to bring together researchers from academia, industry, and government, to create a forum for discussing recent advances in graph analysis. In doing so, we aim to better understand the overarching principles and the limitations of our current methods and to inspire research on new algorithms and techniques for mining and learning with graphs.</span></p><p dir="ltr" style="line-height:1.38;margin-top:12pt;margin-bottom:12pt;text-align:left"><span style="font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap">To reflect the broad scope of work on mining and learning with graphs, we encourage submissions that span the spectrum from theoretical analysis to algorithms and implementation, to applications and empirical studies. As an example, the growth of user-generated content on blogs, microblogs, discussion forums, product reviews, etc., has given rise to a host of new opportunities for graph mining in the analysis of social media. We encourage submissions on theory, methods, and applications focusing on a broad range of graph-based approaches in various domains.</span></p><p dir="ltr" style="line-height:1.38;margin-top:12pt;margin-bottom:12pt;text-align:left"><span style="font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap">Topics of interest include, but are not limited to:</span></p><ul style="margin-top:0px;margin-bottom:0px;text-align:left"><li dir="ltr" style="list-style-type:disc;font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre"><p dir="ltr" style="line-height:1.38;margin-top:12pt;margin-bottom:0pt"><span style="font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap">Theoretical aspects:</span></p></li><ul style="margin-top:0px;margin-bottom:0px"><li dir="ltr" style="list-style-type:circle;font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre"><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap">Computational or statistical learning theory related to graphs</span></p></li><li dir="ltr" style="list-style-type:circle;font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre"><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap">Theoretical analysis of graph algorithms or models</span></p></li><li dir="ltr" style="list-style-type:circle;font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre"><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap">Sampling and evaluation issues in graph algorithms</span></p></li><li dir="ltr" style="list-style-type:circle;font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre"><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap">Analysis of dynamic graphs</span></p></li></ul><li dir="ltr" style="list-style-type:disc;font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre"><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap">Algorithms and methods:</span></p></li><ul style="margin-top:0px;margin-bottom:0px"><li dir="ltr" style="list-style-type:circle;font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre"><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap">Graph mining</span></p></li><li dir="ltr" style="list-style-type:circle;font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre"><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap">Probabilistic and graphical models for structured data</span></p></li><li dir="ltr" style="list-style-type:circle;font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre"><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap">Heterogeneous/multi-model graph analysis</span></p></li><li dir="ltr" style="list-style-type:circle;font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre"><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap">Network embedding models</span></p></li><li dir="ltr" style="list-style-type:circle;font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre"><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap">Statistical models of graph structure</span></p></li><li dir="ltr" style="list-style-type:circle;font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre"><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap">Combinatorial graph methods</span></p></li><li dir="ltr" style="list-style-type:circle;font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre"><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap">Semi-supervised learning, active learning, transductive inference, and transfer learning in the context of graph</span></p></li></ul><li dir="ltr" style="list-style-type:disc;font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre"><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap">Applications and analysis:</span></p></li><ul style="margin-top:0px;margin-bottom:0px"><li dir="ltr" style="list-style-type:circle;font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre"><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap">Analysis of social media</span></p></li><li dir="ltr" style="list-style-type:circle;font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre"><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap">Analysis of biological networks</span></p></li><li dir="ltr" style="list-style-type:circle;font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre"><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap">Knowledge graph construction</span></p></li><li dir="ltr" style="list-style-type:circle;font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre"><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:12pt"><span style="font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap">Large-scale analysis and modeling</span></p></li></ul></ul><p dir="ltr" style="line-height:1.38;margin-top:12pt;margin-bottom:12pt;text-align:left"><span style="font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap">We welcome many kinds of papers, such as, but not limited to:</span></p><ul style="margin-top:0px;margin-bottom:0px;text-align:left"><li dir="ltr" style="list-style-type:disc;font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre"><p dir="ltr" style="line-height:1.38;margin-top:12pt;margin-bottom:0pt"><span style="font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap">Novel research papers</span></p></li><li dir="ltr" style="list-style-type:disc;font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre"><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap">Demo papers</span></p></li><li dir="ltr" style="list-style-type:disc;font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre"><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap">Work-in-progress papers</span></p></li><li dir="ltr" style="list-style-type:disc;font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre"><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap">Visionary papers (white papers)</span></p></li><li dir="ltr" style="list-style-type:disc;font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre"><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap">Appraisal papers of existing methods and tools (e.g., lessons learned)</span></p></li><li dir="ltr" style="list-style-type:disc;font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:700;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre"><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:700;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap">Relevant work that has been previously published</span></p></li><li dir="ltr" style="list-style-type:disc;font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:700;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre"><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:12pt"><span style="font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:700;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap">Work that will be presented at the main conference</span></p></li></ul><div style="text-align:left"><br></div><p dir="ltr" style="line-height:1.656;margin-top:0pt;margin-bottom:0pt;text-align:left"><span style="font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap">Authors should </span><span style="font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:700;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap">clearly indicate</span><span style="font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap"> in their abstracts the kinds of submissions that the papers belong to, to help reviewers better understand their contributions. Submissions must be in PDF,</span><span style="font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:700;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap"> no more than 8 pages long</span><span style="font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap"> — shorter papers are welcome — and formatted according to the standard double-column</span><a href="http://www.acm.org/publications/proceedings-template#aL2" style="text-decoration:none"><span style="font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap"> </span><span style="font-size:11pt;font-family:Arial;color:rgb(17,85,204);background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:underline;vertical-align:baseline;white-space:pre-wrap">ACM Proceedings Style</span></a><span style="font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap">. The accepted papers will be published on the workshop’s website and will not be considered archival for re-submission purposes. Authors whose papers are accepted to the workshop will have the opportunity to participate in a spotlight and poster session, and some set will also be chosen for oral presentation. </span></p><div style="text-align:left"><br></div><p dir="ltr" style="line-height:1.656;margin-top:0pt;margin-bottom:0pt;text-align:left"><span style="font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:700;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap">Timeline:</span></p><p dir="ltr" style="line-height:1.656;margin-top:0pt;margin-bottom:0pt;text-align:left"><span style="font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap">Submission Deadline: June 15, 2020</span></p><p dir="ltr" style="line-height:1.656;margin-top:0pt;margin-bottom:0pt;text-align:left"><span style="font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap">Notification: July 15, 2020</span></p><p dir="ltr" style="line-height:1.656;margin-top:0pt;margin-bottom:0pt;text-align:left"><span style="font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap">Final Version: August 1, 2020</span></p><p dir="ltr" style="line-height:1.656;margin-top:0pt;margin-bottom:0pt;text-align:left"><span style="font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap">Workshop: August 24, 2020</span></p><div style="text-align:left"><br></div><p dir="ltr" style="line-height:1.656;margin-top:0pt;margin-bottom:0pt;text-align:left"><span style="font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap">Submission instructions can be found on</span><a href="http://www.mlgworkshop.org/2018/" style="text-decoration:none"><span style="font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap"> </span><span style="font-size:11pt;font-family:Arial;color:rgb(17,85,204);background-color:transparent;font-weight:700;font-style:normal;font-variant:normal;text-decoration:underline;vertical-align:baseline;white-space:pre-wrap">http://www.mlgworkshop.org/2020/</span></a></p><p dir="ltr" style="line-height:1.656;margin-top:0pt;margin-bottom:0pt;text-align:left"><span style="font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:700;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap">Please send enquiries to </span><span style="font-size:11pt;font-family:Arial;color:rgb(17,85,204);background-color:transparent;font-weight:700;font-style:normal;font-variant:normal;text-decoration:underline;vertical-align:baseline;white-space:pre-wrap"><a href="mailto:chair@mlgworkshop.org">chair@mlgworkshop.org</a></span></p><div style="text-align:left"><br></div><p dir="ltr" style="line-height:1.656;margin-top:0pt;margin-bottom:0pt;text-align:left"><span style="font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:700;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap">Organizers:</span></p><p dir="ltr" style="line-height:1.656;margin-top:0pt;margin-bottom:0pt;text-align:left"><span style="font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap">Shobeir Fakhraei (Amazon)</span></p><p dir="ltr" style="line-height:1.656;margin-top:0pt;margin-bottom:0pt;text-align:left"><span style="font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap">Aude Hofleitner (Facebook) </span></p><p dir="ltr" style="line-height:1.656;margin-top:0pt;margin-bottom:0pt;text-align:left"><span style="font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap">Julian McAuley (University of California, San Diego)</span></p><p dir="ltr" style="line-height:1.656;margin-top:0pt;margin-bottom:0pt;text-align:left"><span style="font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap">Bryan Perozzi (Google Research)</span></p><p dir="ltr" style="line-height:1.656;margin-top:0pt;margin-bottom:0pt;text-align:left"><span style="font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap">Tim Weninger (University of Notre Dame)</span></p><div style="text-align:left"><br><br></div><p dir="ltr" style="line-height:1.656;margin-top:0pt;margin-bottom:0pt;text-align:left"><span style="font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:700;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap">Program Committee:</span></p><p dir="ltr" style="line-height:1.656;margin-top:0pt;margin-bottom:0pt;text-align:left"><span style="font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap">Siddharth Bhatia (National University of Singapore), Jundong Li (University of Virginia), Xin-Zeng Wu (Information Sciences Institute), Stefano Leucci (University of L'Aquila), Jin Kyu Kim (Facebook), Hocine Cherifi (University of Burgundy), Dhivya Eswaran (Amazon), Ting Chen (University of California, Los Angeles), Ivan Brugere (University of Illinois at Chicago), Yuan Fang (Singapore Management University), Blaz Novak (Jozef Stefan Institute), Sucheta Soundarajan (Syracuse University), Fred Morstatter (University of Southern California), Acar Tamersoy (NortonLifeLock Research Group), John Palowitch (Google), Austin Benson (Cornell University), Hanghang Tong (University of Illinois at Urbana-Champaign), Larry Holder (Washington State University), Aaron Clauset (University of Colorado Boulder), Jan Ramon (INRIA), Christian Bauckhage (Fraunhofer), Bryan Hooi (National University of Singapore), William Hamilton (Stanford University), Aris Anagnostopoulos (Sapienza University of Rome), Ulf Brefeld (Leuphana Universität Lüneburg), Ali Pinar (Sandia National Laboratories), Alessandro Epasto (Google), Danai Koutra (University of Michigan), Evangelos Papalexakis (University of California Riverside), Stefan Wrobel (Fraunhofer IAIS & Univ. of Bonn), Ana Paula Appel (IBM Research Brazil), Marco Bressan (Sapienza University of Rome)</span></p><div style="text-align:left"><br></div><p dir="ltr" style="line-height:1.656;margin-top:0pt;margin-bottom:0pt;text-align:left"><span style="font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap">To receive updates about the current and future workshops and the Graph Mining community, please join the mailing list:</span><a href="https://groups.google.com/d/forum/mlg-list" style="text-decoration:none"><span style="font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap"> </span><span style="font-size:11pt;font-family:Arial;color:rgb(17,85,204);background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:underline;vertical-align:baseline;white-space:pre-wrap">https://groups.google.com/d/forum/mlg-list</span></a><span style="font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap">   </span></p><p dir="ltr" style="line-height:1.656;margin-top:0pt;margin-bottom:0pt;text-align:left"><span style="font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap">or follow the twitter account:</span><a href="https://twitter.com/mlgworkshop" style="text-decoration:none"><span style="font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap"> </span><span style="font-size:11pt;font-family:Arial;color:rgb(17,85,204);background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:underline;vertical-align:baseline;white-space:pre-wrap">https://twitter.com/mlgworkshop</span></a></p><div style="text-align:left"><br></div><p dir="ltr" style="line-height:1.656;margin-top:0pt;margin-bottom:0pt;text-align:left"><span style="font-size:11pt;font-family:Arial;color:rgb(0,0,0);background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap">We look forward to seeing you at the workshop!</span></p></div>