<html xmlns:v="urn:schemas-microsoft-com:vml" xmlns:o="urn:schemas-microsoft-com:office:office" xmlns:w="urn:schemas-microsoft-com:office:word" xmlns:m="http://schemas.microsoft.com/office/2004/12/omml" xmlns="http://www.w3.org/TR/REC-html40"><head><meta http-equiv=Content-Type content="text/html; charset=iso-8859-1"><meta name=Generator content="Microsoft Word 15 (filtered medium)"><style><!--
/* Font Definitions */
@font-face
{font-family:"Cambria Math";
panose-1:2 4 5 3 5 4 6 3 2 4;}
@font-face
{font-family:Calibri;
panose-1:2 15 5 2 2 2 4 3 2 4;}
/* Style Definitions */
p.MsoNormal, li.MsoNormal, div.MsoNormal
{margin:0cm;
font-size:11.0pt;
font-family:"Calibri",sans-serif;
mso-fareast-language:EN-US;}
a:link, span.MsoHyperlink
{mso-style-priority:99;
color:#0563C1;
text-decoration:underline;}
span.StileMessaggioDiPostaElettronica17
{mso-style-type:personal-compose;
font-family:"Calibri",sans-serif;
color:windowtext;}
.MsoChpDefault
{mso-style-type:export-only;
font-family:"Calibri",sans-serif;
mso-fareast-language:EN-US;}
@page WordSection1
{size:612.0pt 792.0pt;
margin:70.85pt 2.0cm 2.0cm 2.0cm;}
div.WordSection1
{page:WordSection1;}
--></style><!--[if gte mso 9]><xml>
<o:shapedefaults v:ext="edit" spidmax="1026" />
</xml><![endif]--><!--[if gte mso 9]><xml>
<o:shapelayout v:ext="edit">
<o:idmap v:ext="edit" data="1" />
</o:shapelayout></xml><![endif]--></head><body lang=IT link="#0563C1" vlink="#954F72" style='word-wrap:break-word'><div class=WordSection1><p class=MsoNormal><span lang=EN-US>*** ACM SAC 2022 ***<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US><o:p> </o:p></span></p><p class=MsoNormal><span lang=EN-US>===============<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US>Graph Models for Learning and Recognition (GMLR) Track<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US>The 37th ACM Symposium on Applied Computing (SAC 2022)<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US>April 25-29, 2022, Brno, Czech Republic<o:p></o:p></span></p><p class=MsoNormal><a href="http://phuselab.di.unimi.it/GMLR2022"><span lang=EN-US>http://phuselab.di.unimi.it/GMLR2022</span></a><span lang=EN-US><o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US><o:p> </o:p></span></p><p class=MsoNormal><span lang=EN-US>MOTIVATIONS AND TOPICS<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US>======================<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US>The ACM Symposium on Applied Computing (SAC 2022) has been a primary gathering forum for applied computer scientists, computer engineers, software engineers, and application developers from around the world. SAC 2022 is sponsored by the ACM Special Interest Group on Applied Computing (SIGAPP), and will be held in Brno, Czech Republic. The technical track on Graph Models for Learning and Recognition (GMLR) is the first edition and is organized within SAC 2022. Graphs have gained a lot of attention in the pattern recognition community thanks to their ability to encode both topological and semantic information. Encouraged by the success of CNNs, a wide variety of methods have redefined the notion of convolution for graphs. These new approaches have in general enabled effective training and achieved in many cases better performances than competitors, though at the detriment of computational costs. Typical examples of applications dealing with graph-based representation are: scene graph generation, point clouds classification, and action recognition in computer vision; text classification, inter-relations of documents or words to infer document labels in natural language processing; forecasting traffic speed, volume or the density of roads in traffic networks, whereas in chemistry researchers apply graph-based algorithms to study the graph structure of molecules/compounds.<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US><o:p> </o:p></span></p><p class=MsoNormal><span lang=EN-US>This track intends to focus on all aspects of graph-based representations and models for learning and recognition tasks. GMLR spans, but is not limited to, the following topics:<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US><o:p> </o:p></span></p><p class=MsoNormal><span lang=EN-US>- Graph Neural Networks: theory and applications<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US>- Deep learning on graphs<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US>- Graph or knowledge representational learning<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US>- Graphs in pattern recognition<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US>- Graph databases and linked data in AI<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US>- Benchmarks for GNN<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US>- Dynamic, spatial and temporal graphs<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US>- Graph methods in computer vision<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US>- Human behavior and scene understanding<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US>- Social networks analysis<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US>- Data fusion methods in GNN<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US>- Efficient and parallel computation for graph learning algorithms<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US>- Reasoning over knowledge-graphs<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US>- Interactivity, explainability and trust in graph-based learning<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US>- Probabilistic graphical models<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US>- Biomedical data analytics on graphs<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US><o:p> </o:p></span></p><p class=MsoNormal><span lang=EN-US>Authors of selected top papers of this track will be asked to publish an extended version in a Special Issue of a Journal (the journal will be announced soon).<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US><o:p> </o:p></span></p><p class=MsoNormal><span lang=EN-US>IMPORTANT DATES<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US>===============<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US>Submission of regular papers: October 15, 2021<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US>Notification of acceptance/rejection: December 10, 2021<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US>Camera-ready copies of accepted papers: December 21, 2021<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US>SAC Conference: April 25 - 29, 2022<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US><o:p> </o:p></span></p><p class=MsoNormal><span lang=EN-US>SUBMISSION GUIDELINES<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US>=====================<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US>Authors are invited to submit original and unpublished papers of research and applications for this track. The author(s) name(s) and address(es) must not appear in the body of the paper, and self-reference should be in the third person. This is to facilitate double-blind review. Please, visit the website for more information about submission<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US><o:p> </o:p></span></p><p class=MsoNormal><span lang=EN-US>SAC NO-SHOW POLICY<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US>==================<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US>Paper registration is required, allowing the inclusion of the paper/poster in the conference proceedings. An author or a proxy attending SAC MUST present the paper. This is a requirement for the paper/poster to be included in the ACM digital library. No-show of registered papers and posters will result in excluding them from the ACM digital library.<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US><o:p> </o:p></span></p><p class=MsoNormal><span lang=EN-US>TRACK CHAIRS<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US>============<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US>Donatello Conte (University of Tours)<o:p></o:p></span></p><p class=MsoNormal>Giuliano Grossi (University of Milan)<o:p></o:p></p><p class=MsoNormal>Raffaella Lanzarotti (University of Milan)<o:p></o:p></p><p class=MsoNormal>Jianyi Lin (Università Cattolica del Sacro Cuore)<o:p></o:p></p><p class=MsoNormal><span lang=EN-US>Jean-Yves Ramel (University of Tours) <o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US><o:p> </o:p></span></p><p class=MsoNormal><span lang=EN-US><o:p> </o:p></span></p></div></body></html>