<div dir="ltr"><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap"><font face="arial, sans-serif">Dear all,</font></span></p><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap"><font face="arial, sans-serif"> </font></span></p><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><font face="arial, sans-serif"><span style="color:rgb(0,0,0);background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap">We are excited to announce the third iteration of our workshop “</span><span style="color:rgb(0,0,0);background-color:transparent;font-weight:700;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap">Sparsity in Neural Networks: On practical limitations and tradeoffs between sustainability and efficiency</span><span style="color:rgb(0,0,0);background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap">”,</span><span style="color:rgb(0,0,0);background-color:transparent;font-weight:700;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap"> at ICLR’23</span><span style="color:rgb(0,0,0);background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap"> continuing on its successful inaugural version in 2021 and 2022. The workshop will take place in a hybrid manner on May 5th, 2023 in Kigali, Rwanda.</span></font></p><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap"><font face="arial, sans-serif"> </font></span></p><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><font face="arial, sans-serif"><span style="color:rgb(0,0,0);background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap">The goal of the workshop is to bring together members of many communities working on neural network sparsity to share their perspectives and the latest cutting-edge research. We have assembled an incredible group of speakers, and </span><span style="color:rgb(0,0,0);background-color:transparent;font-weight:700;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap">we are seeking contributed work from the community. </span></font></p><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap"><font face="arial, sans-serif"> </font></span></p><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><font face="arial, sans-serif"><span style="color:rgb(0,0,0);background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap">For more information and submitting your paper, please visit the workshop website: </span><a href="https://www.sparseneural.net/" target="_blank" style="text-decoration-line:none"><span style="background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;text-decoration-line:underline;vertical-align:baseline;white-space:pre-wrap">https://www.sparseneural.net/</span></a></font></p><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><font face="arial, sans-serif"> </font></p><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><font face="arial, sans-serif"> </font></p><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:6pt"><span style="color:rgb(0,0,0);background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap"><font face="arial, sans-serif" size="4">Important Dates</font></span></p><ul style="margin-top:0px;margin-bottom:0px"><li dir="ltr" style="margin-left:11pt;list-style-type:disc;color:rgb(0,0,0);background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap"><p dir="ltr" role="presentation" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline"><font face="arial, sans-serif">February 3th, 2023 [AOE]: Submit an abstract and supporting materials</font></span></p></li><li dir="ltr" style="margin-left:11pt;list-style-type:disc;color:rgb(0,0,0);background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap"><p dir="ltr" role="presentation" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline"><font face="arial, sans-serif">March 3th, 2023: Notification of acceptance</font></span></p></li><li dir="ltr" style="margin-left:11pt;list-style-type:disc;color:rgb(0,0,0);background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap"><p dir="ltr" role="presentation" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline"><font face="arial, sans-serif">May 5, 2023: Workshop</font></span></p></li></ul><div><br></div><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:6pt"><span style="color:rgb(0,0,0);background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap"><font face="arial, sans-serif" size="4">Topics (including but not limited to)</font></span></p><ul style="margin-top:0px;margin-bottom:0px"><li dir="ltr" style="margin-left:11pt;list-style-type:disc;color:rgb(0,0,0);background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap"><p dir="ltr" role="presentation" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline"><font face="arial, sans-serif">Algorithms for Sparsity</font></span></p></li></ul><ul style="margin-top:0px;margin-bottom:0px"><li dir="ltr" style="margin-left:47pt;list-style-type:circle;color:rgb(0,0,0);background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap"><p dir="ltr" role="presentation" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline"><font face="arial, sans-serif">Pruning both for post-training inference, and during training</font></span></p></li><li dir="ltr" style="margin-left:47pt;list-style-type:circle;color:rgb(0,0,0);background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap"><p dir="ltr" role="presentation" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline"><font face="arial, sans-serif">Algorithms for fully sparse training (fixed or dynamic), including biologically inspired algorithms</font></span></p></li><li dir="ltr" style="margin-left:47pt;list-style-type:circle;color:rgb(0,0,0);background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap"><p dir="ltr" role="presentation" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline"><font face="arial, sans-serif">Algorithms for ephemeral (activation) sparsity</font></span></p></li><li dir="ltr" style="margin-left:47pt;list-style-type:circle;color:rgb(33,33,33);background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap"><p dir="ltr" role="presentation" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="color:rgb(0,0,0);background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline"><font face="arial, sans-serif">Sparsely activated expert models</font></span></p></li><li dir="ltr" style="margin-left:47pt;list-style-type:circle;color:rgb(33,33,33);background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap"><p dir="ltr" role="presentation" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="color:rgb(0,0,0);background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline"><font face="arial, sans-serif">Scaling laws for sparsity</font></span></p></li><li dir="ltr" style="margin-left:47pt;list-style-type:circle;color:rgb(33,33,33);background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap"><p dir="ltr" role="presentation" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="color:rgb(0,0,0);background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline"><font face="arial, sans-serif">Sparsity in deep reinforcement learning</font></span></p></li></ul><ul style="margin-top:0px;margin-bottom:0px"><li dir="ltr" style="margin-left:11pt;list-style-type:disc;color:rgb(0,0,0);background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap"><p dir="ltr" role="presentation" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline"><font face="arial, sans-serif">Systems for Sparsity</font></span></p></li></ul><ul style="margin-top:0px;margin-bottom:0px"><li dir="ltr" style="margin-left:47pt;list-style-type:circle;color:rgb(0,0,0);background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap"><p dir="ltr" role="presentation" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline"><font face="arial, sans-serif">Libraries, kernels, and compilers for accelerating sparse computation</font></span></p></li><li dir="ltr" style="margin-left:47pt;list-style-type:circle;color:rgb(0,0,0);background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap"><p dir="ltr" role="presentation" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline"><font face="arial, sans-serif">Hardware with support for sparse computation</font></span></p></li></ul><ul style="margin-top:0px;margin-bottom:0px"><li dir="ltr" style="margin-left:11pt;list-style-type:disc;color:rgb(0,0,0);background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap"><p dir="ltr" role="presentation" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline"><font face="arial, sans-serif">Theory and Science of Sparsity</font></span></p></li></ul><ul style="margin-top:0px;margin-bottom:0px"><li dir="ltr" style="margin-left:47pt;list-style-type:circle;color:rgb(0,0,0);background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap"><p dir="ltr" role="presentation" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline"><font face="arial, sans-serif">When is overparameterization necessary (or not)</font></span></p></li><li dir="ltr" style="margin-left:47pt;list-style-type:circle;color:rgb(0,0,0);background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap"><p dir="ltr" role="presentation" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline"><font face="arial, sans-serif">Optimization behavior of sparse networks</font></span></p></li><li dir="ltr" style="margin-left:47pt;list-style-type:circle;color:rgb(0,0,0);background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap"><p dir="ltr" role="presentation" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline"><font face="arial, sans-serif">Representation ability of sparse networks</font></span></p></li><li dir="ltr" style="margin-left:47pt;list-style-type:circle;color:rgb(0,0,0);background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap"><p dir="ltr" role="presentation" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline"><font face="arial, sans-serif">Sparsity and generalization</font></span></p></li><li dir="ltr" style="margin-left:47pt;list-style-type:circle;color:rgb(0,0,0);background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap"><p dir="ltr" role="presentation" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline"><font face="arial, sans-serif">The stability of sparse models</font></span></p></li><li dir="ltr" style="margin-left:47pt;list-style-type:circle;color:rgb(0,0,0);background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap"><p dir="ltr" role="presentation" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline"><font face="arial, sans-serif">Forgetting owing to sparsity, including fairness, privacy and bias concerns</font></span></p></li><li dir="ltr" style="margin-left:47pt;list-style-type:circle;color:rgb(0,0,0);background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap"><p dir="ltr" role="presentation" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline"><font face="arial, sans-serif">Connecting neural network sparsity with traditional sparse dictionary modeling</font></span></p></li></ul><ul style="margin-top:0px;margin-bottom:0px"><li dir="ltr" style="margin-left:11pt;list-style-type:disc;color:rgb(0,0,0);background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap"><p dir="ltr" role="presentation" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline"><font face="arial, sans-serif">Applications for Sparsity</font></span></p></li></ul><ul style="margin-top:0px;margin-bottom:0px"><li dir="ltr" style="margin-left:47pt;list-style-type:circle;color:rgb(0,0,0);background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap"><p dir="ltr" role="presentation" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline"><font face="arial, sans-serif">Resource-efficient learning at the edge or the cloud</font></span></p></li><li dir="ltr" style="margin-left:47pt;list-style-type:circle;color:rgb(0,0,0);background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap"><p dir="ltr" role="presentation" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline"><font face="arial, sans-serif">Data-efficient learning for sparse models</font></span></p></li><li dir="ltr" style="margin-left:47pt;list-style-type:circle;color:rgb(0,0,0);background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap"><p dir="ltr" role="presentation" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline"><font face="arial, sans-serif">Communication-efficient distributed or federated learning with sparse models </font></span></p></li><li dir="ltr" style="margin-left:47pt;list-style-type:circle;color:rgb(0,0,0);background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap"><p dir="ltr" role="presentation" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline"><font face="arial, sans-serif">Graph and network science applications</font></span></p></li></ul><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap"><font face="arial, sans-serif"> </font></span></p><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="color:rgb(0,0,0);background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap"><font face="arial, sans-serif">This workshop is non-archival, and it will not have proceedings. </font></span></p><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><font face="arial, sans-serif"> </font></p><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="color:rgb(0,0,0);background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap"><font face="arial, sans-serif" size="4">Submissions will receive one of three possible decisions:</font></span></p><ul style="margin-top:0px;margin-bottom:0px"><li dir="ltr" style="margin-left:11pt;list-style-type:disc;color:rgb(0,0,0);background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap"><p dir="ltr" role="presentation" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><font face="arial, sans-serif"><span style="background-color:transparent;font-weight:700;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline">Accept (Spotlight Presentation)</span><span style="background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline">. The authors will be invited to present the work during the main workshop, with live Q&A.</span></font></p></li><li dir="ltr" style="margin-left:11pt;list-style-type:disc;color:rgb(0,0,0);background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap"><p dir="ltr" role="presentation" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><font face="arial, sans-serif"><span style="background-color:transparent;font-weight:700;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline">Accept (Poster Presentation)</span><span style="background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline">. The authors will be invited to present their work as a poster during the workshop’s interactive poster sessions.</span></font></p></li><li dir="ltr" style="margin-left:11pt;list-style-type:disc;color:rgb(0,0,0);background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap"><p dir="ltr" role="presentation" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><font face="arial, sans-serif"><span style="background-color:transparent;font-weight:700;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline">Reject</span><span style="background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline">. The paper will not be presented at the workshop.</span></font></p></li></ul><font face="arial, sans-serif"><br></font><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:6pt"><span style="color:rgb(0,0,0);background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap"><font face="arial, sans-serif" size="4">Eligible Work</font></span></p><ul style="margin-top:0px;margin-bottom:0px"><li dir="ltr" style="margin-left:11pt;list-style-type:disc;color:rgb(0,0,0);background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap"><p dir="ltr" role="presentation" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><font face="arial, sans-serif"><span style="background-color:transparent;font-weight:700;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline">The latest research innovations</span><span style="background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline"> at all stages of the research process, from work-in-progress to recently published papers, where “recent” refers to work presented within one year of the workshop, e.g., the manuscript is first publicly available on arxiv or elsewhere no earlier than February 3, 2022. We permit under-review or concurrent submissions.</span></font></p></li></ul><ul style="margin-top:0px;margin-bottom:0px"><li dir="ltr" style="margin-left:13.5pt;list-style-type:disc;color:rgb(0,0,0);background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap"><p dir="ltr" role="presentation" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><font face="arial, sans-serif"><span style="background-color:transparent;font-weight:700;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline">Position or survey papers</span><span style="background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline"> on any topics relevant to this workshop (see above)</span></font></p></li></ul><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><font face="arial, sans-serif"> </font></p><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="color:rgb(0,0,0);background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap"><font face="arial, sans-serif" size="4">Required materials</font></span></p><ol style="margin-top:0px;margin-bottom:0px"><li dir="ltr" style="margin-left:11pt;list-style-type:decimal;color:rgb(0,0,0);background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap"><p dir="ltr" role="presentation" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><font face="arial, sans-serif"><span style="background-color:transparent;font-weight:700;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline">One mandatory abstract</span><span style="background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline"> (250 words or fewer) describing the work</span></font></p></li><li dir="ltr" style="margin-left:11pt;list-style-type:decimal;color:rgb(0,0,0);background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap"><p dir="ltr" role="presentation" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><font face="arial, sans-serif"><span style="background-color:transparent;font-weight:700;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline">Up-to 8 pages in length excluding the references and the appendix, </span><span style="background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline">for both technical and position papers</span><span style="background-color:transparent;font-weight:700;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline">. </span><span style="background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline">We encourage work-in-progress submissions and expect most submissions to be approximately 4 pages. Papers can be submitted in any of the ICLR, Neurips or ICML conference formats.</span></font></p></li></ol><font face="arial, sans-serif"><br></font><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap"><font face="arial, sans-serif"> </font></span></p><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="color:rgb(0,0,0);background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap"><font face="arial, sans-serif">We hope you will join us in attendance!</font></span></p><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap"><font face="arial, sans-serif"> </font></span></p><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="color:rgb(0,0,0);background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap"><font face="arial, sans-serif">Best Regards,</font></span></p><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:6pt"><span style="color:rgb(0,0,0);background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap"><font face="arial, sans-serif">On behalf of the organizing team (Aleksandra, Atlas, Baharan, Decebal, Elena, Ghada, Trevor, Utku, Zahra)</font></span></p></div>