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</o:shapelayout></xml><![endif]--></head><body lang=EN-US link=blue vlink=purple><div class=WordSection1><p class=MsoHeader align=right style='text-align:right'><o:p> </o:p></p><p class=MsoHeader><b><span style='font-size:20.0pt;font-family:"Cambria",serif'>EE SEMINAR SERIES<o:p></o:p></span></b></p><p class=MsoHeader align=center style='text-align:center'><o:p> </o:p></p><p class=MsoHeader> <o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><table class=MsoNormalTable border=0 cellspacing=0 cellpadding=0 align=left width=0 style='width:527.4pt;border-collapse:collapse;margin-left:6.75pt;margin-right:6.75pt'><tr style='height:.25in'><td width=80 style='width:60.3pt;padding:0in 5.4pt 0in 5.4pt;height:.25in'><p class=MsoNormal style='mso-element:frame;mso-element-frame-hspace:9.0pt;mso-element-wrap:around;mso-element-anchor-vertical:paragraph;mso-element-anchor-horizontal:column;mso-height-rule:exactly'><strong><i><span style='font-family:"Cambria",serif'>Speaker:</span></i></strong><i><span style='font-family:"Cambria",serif'> </span></i><em><span style='font-size:12.0pt;font-family:"Cambria",serif;mso-fareast-language:KO;font-style:normal'><o:p></o:p></span></em></p></td><td width=623 style='width:467.1pt;padding:0in 5.4pt 0in 5.4pt;height:.25in'><p class=MsoNormal style='mso-element:frame;mso-element-frame-hspace:9.0pt;mso-element-wrap:around;mso-element-anchor-vertical:paragraph;mso-element-anchor-horizontal:column;mso-height-rule:exactly'><span style='font-family:"Cambria",serif'>Negar Kiyavash, Georgia Institute of Technology</span><o:p></o:p></p></td></tr><tr style='height:.25in'><td width=80 style='width:60.3pt;padding:0in 5.4pt 0in 5.4pt;height:.25in'><p class=MsoNormal style='mso-element:frame;mso-element-frame-hspace:9.0pt;mso-element-wrap:around;mso-element-anchor-vertical:paragraph;mso-element-anchor-horizontal:column;mso-height-rule:exactly'><strong><i><span style='font-family:"Cambria",serif'>Title:</span></i></strong><i><span style='font-family:"Cambria",serif'> </span></i><em><span style='font-family:"Calibri",sans-serif;mso-fareast-language:KO;font-style:normal'><o:p></o:p></span></em></p></td><td width=623 style='width:467.1pt;padding:0in 5.4pt 0in 5.4pt;height:.25in'><p class=MsoNormal style='mso-element:frame;mso-element-frame-hspace:9.0pt;mso-element-wrap:around;mso-element-anchor-vertical:paragraph;mso-element-anchor-horizontal:column;mso-height-rule:exactly'><span style='font-family:"Cambria",serif'>Network Inference: from Passive to Active Learning</span><o:p></o:p></p></td></tr><tr style='height:.25in'><td width=80 style='width:60.3pt;padding:0in 5.4pt 0in 5.4pt;height:.25in'><p class=MsoNormal style='mso-element:frame;mso-element-frame-hspace:9.0pt;mso-element-wrap:around;mso-element-anchor-vertical:paragraph;mso-element-anchor-horizontal:column;mso-height-rule:exactly'><strong><i><span style='font-family:"Cambria",serif'>Day:</span></i></strong><i><span style='font-family:"Cambria",serif'> </span></i><em><span style='font-family:"Calibri",sans-serif;font-style:normal'><o:p></o:p></span></em></p></td><td width=623 style='width:467.1pt;padding:0in 5.4pt 0in 5.4pt;height:.25in'><p class=MsoNormal style='mso-element:frame;mso-element-frame-hspace:9.0pt;mso-element-wrap:around;mso-element-anchor-vertical:paragraph;mso-element-anchor-horizontal:column;mso-height-rule:exactly'><span class=date-display-single><span style='font-family:"Cambria",serif'>Wednesday, October 17, 2018</span></span><em><b><span style='font-size:12.0pt;font-family:"Cambria",serif;mso-fareast-language:KO;font-style:normal'><o:p></o:p></span></b></em></p></td></tr><tr style='height:.25in'><td width=80 style='width:60.3pt;padding:0in 5.4pt 0in 5.4pt;height:.25in'><p class=MsoNormal style='mso-element:frame;mso-element-frame-hspace:9.0pt;mso-element-wrap:around;mso-element-anchor-vertical:paragraph;mso-element-anchor-horizontal:column;mso-height-rule:exactly'><strong><i><span style='font-family:"Cambria",serif'>Time:</span></i></strong><strong><i><span style='font-family:"Calibri",sans-serif'><o:p></o:p></span></i></strong></p></td><td width=623 style='width:467.1pt;padding:0in 5.4pt 0in 5.4pt;height:.25in'><p class=MsoNormal style='mso-element:frame;mso-element-frame-hspace:9.0pt;mso-element-wrap:around;mso-element-anchor-vertical:paragraph;mso-element-anchor-horizontal:column;mso-height-rule:exactly'><em><span style='font-family:"Cambria",serif;font-style:normal'>4:30 pm</span></em><em><span style='font-family:"Calibri",sans-serif'><o:p></o:p></span></em></p></td></tr><tr style='height:.25in'><td width=80 style='width:60.3pt;padding:0in 5.4pt 0in 5.4pt;height:.25in'><p class=MsoNormal style='mso-element:frame;mso-element-frame-hspace:9.0pt;mso-element-wrap:around;mso-element-anchor-vertical:paragraph;mso-element-anchor-horizontal:column;mso-height-rule:exactly'><strong><i><span style='font-family:"Cambria",serif'>Room:</span></i></strong><i><span style='font-family:"Cambria",serif'> </span></i><em><span style='font-size:12.0pt;font-family:"Cambria",serif;mso-fareast-language:KO;font-style:normal'><o:p></o:p></span></em></p></td><td width=623 style='width:467.1pt;padding:0in 5.4pt 0in 5.4pt;height:.25in'><p class=MsoNormal style='mso-element:frame;mso-element-frame-hspace:9.0pt;mso-element-wrap:around;mso-element-anchor-vertical:paragraph;mso-element-anchor-horizontal:column;mso-height-rule:exactly'><em><span style='font-family:"Cambria",serif;font-style:normal'>B205 Engineering Quadrangle</span></em><em><span style='font-size:12.0pt;font-family:"Cambria",serif;mso-fareast-language:KO;font-style:normal'><o:p></o:p></span></em></p></td></tr><tr style='height:.25in'><td width=80 style='width:60.3pt;padding:0in 5.4pt 0in 5.4pt;height:.25in'><p class=MsoNormal style='mso-element:frame;mso-element-frame-hspace:9.0pt;mso-element-wrap:around;mso-element-anchor-vertical:paragraph;mso-element-anchor-horizontal:column;mso-height-rule:exactly'><strong><i><span style='font-family:"Cambria",serif'>Host:</span></i></strong><strong><i><span style='font-family:"Calibri",sans-serif'><o:p></o:p></span></i></strong></p></td><td width=623 style='width:467.1pt;padding:0in 5.4pt 0in 5.4pt;height:.25in'><p class=MsoNormal style='mso-element:frame;mso-element-frame-hspace:9.0pt;mso-element-wrap:around;mso-element-anchor-vertical:paragraph;mso-element-anchor-horizontal:column;mso-height-rule:exactly'><em><span style='font-family:"Cambria",serif;font-style:normal'>Prof. H. Vincent Poor</span></em><em><span style='font-family:"Calibri",sans-serif'><o:p></o:p></span></em></p></td></tr></table><p class=MsoNormal><span style='font-family:"Cambria",serif;mso-fareast-language:KO'><o:p> </o:p></span></p><p class=MsoNormal><span style='font-family:"Cambria",serif'><o:p> </o:p></span></p><p class=MsoNormal><b><span style='font-family:"Cambria",serif'><o:p> </o:p></span></b></p><p class=MsoNormal><b><span style='font-family:"Cambria",serif'><o:p> </o:p></span></b></p><p class=MsoNormal><b><span style='font-family:"Cambria",serif'><o:p> </o:p></span></b></p><p class=MsoNormal><b><span style='font-family:"Cambria",serif'><o:p> </o:p></span></b></p><p class=MsoNormal><b><span style='font-family:"Cambria",serif'><o:p> </o:p></span></b></p><p class=MsoNormal><b><span style='font-family:"Cambria",serif'><o:p> </o:p></span></b></p><p class=MsoNormal><b><span style='font-family:"Cambria",serif'><o:p> </o:p></span></b></p><p class=MsoNormal><b><span style='font-family:"Cambria",serif'><o:p> </o:p></span></b></p><p class=MsoNormal><b><span style='font-family:"Cambria",serif'>Abstract:<o:p></o:p></span></b></p><p class=MsoNormal><span style='font-family:"Cambria",serif'>One of the paramount challenges of this century is that of understanding complex, dynamic, large-scale networks. Such high-dimensional networks, including social, financial, and biological networks, cover the planet and dominate modern life. In this talk, we propose novel approaches to inference in such networks, for both active (interventional) and passive (observational) learning scenarios. We highlight how timing could be utilized as a degree of freedom that provides rich information about the dynamics. This information allows resolving direction of causation even when only a subset of the nodes is observed (latent setting). In the presence of large data, we propose algorithms that identify optimal or near-optimal approximations to the topology of the network often by harnessing side information about the model class.<o:p></o:p></span></p><p class=MsoNormal><b><span style='font-family:"Cambria",serif'><o:p> </o:p></span></b></p><p class=MsoNormal><b><span style='font-family:"Cambria",serif'>Bio:<br></span></b><span style='font-family:"Cambria",serif'>Negar Kiyavash is a joint Associate Professor in the H. Milton Stewart School of Industrial & Systems Engineering (ISyE) and the School of Electrical and Computer Engineering (ECE) at Georgia Institute of Technology (Gatech). Prior to joining Gatech, when was a Willett Faculty Scholar and a joint Associate Professor of Industrial and Enterprise Engineering (IE) and Electrical and Computer Engineering (ECE) at the University of Illinois . Her research interests are in design and analysis of algorithms for network inference and security. She is a recipient of NSF CAREER and AFOSR YIP awards and the Illinois College of Engineering Dean's Award for Excellence in Research.<o:p></o:p></span></p></div></body></html>