<div dir="ltr"><div dir="ltr"><div class="gmail_default" style="font-size:small"><div class="gmail_default"><b>When</b>: Monday, October 28th from<b style="background-color:rgb(255,255,0)"> 11</b><b><span style="background-color:rgb(255,255,0)">am - 12pm CT</span></b></div><div class="gmail_default"><div><b><br></b></div><div><b>Where</b>: Talk will be given <b><font color="#0000ff">live, in-person</font></b> at<br> TTIC, 6045 S. Kenwood Avenue<br> 5th Floor, <b><u><font color="#000000">Room 530</font></u></b></div><div><br><b>Virtually</b>: <i><font color="#0000ff">tba</font></i><br></div><div> </div><div><b>Who: </b> Nina Balcan, Carnegie Mellon University</div><div><br></div></div><div class="gmail_default"><div style="border-top:none;border-right:none;border-left:none;border-bottom:2.25pt solid rgb(11,118,159);padding:0in 0in 1pt"></div><div><font face="arial, sans-serif"><b><br></b></font></div><div><div style="color:rgb(0,0,0);margin-top:0px;margin-bottom:0px"><span style="font-family:arial,sans-serif;color:rgb(51,51,51)"><b>Title: </b>Online learning in </span><span style="font-family:arial,sans-serif;color:rgb(51,51,51)">Stackelberg Security Games</span></div></div></div><div><span style="color:rgb(51,51,51)"><font face="arial, sans-serif"><br></font></span></div><div dir="ltr"><font face="arial, sans-serif"><span style="color:rgb(51,51,51)"><b>Abstract:</b> In a Stackelberg Security Game, a defender commits to a randomized deployment of security resources, and an attacker best responds by attacking a target that maximizes their utility. While algorithms for computing an optimal strategy for the defender to commit to have been used in several real-world applications, deployed applications require knowledge about the utility function of the potential attacker. In this talk I will describe an online learning approach for addressing this problem. We consider algorithms that prescribe a randomized strategy for the defender at each step against an adversarially chosen sequence of attackers and obtain feedback on their choices. I will discuss online algorithms whose regret (when compared to the best fixed strategy in hindsight) is sublinear in the number of time steps. I will also consider an extension that handles auxiliary contextual information that is often readily available to each player (e.g. traffic patterns or weather conditions) and discuss what no regret guarantees are possible in this even more realistic scenario.</span><br style="box-sizing:border-box;color:rgb(51,51,51)"><br style="box-sizing:border-box;color:rgb(51,51,51)"><strong style="box-sizing:border-box;margin:0px;padding:0px;border:0px;font-variant-numeric:inherit;font-variant-east-asian:inherit;font-variant-alternates:inherit;font-stretch:inherit;line-height:inherit;font-size-adjust:inherit;font-kerning:inherit;font-feature-settings:inherit;vertical-align:baseline;color:rgb(51,51,51)">Bio: </strong><span style="color:rgb(51,51,51)">Maria Florina Balcan is the Cadence Design Systems Professor of Computer Science in the School of Computer Science at Carnegie Mellon University. Her main research interests are machine learning, artificial intelligence, theory of computing, and algorithmic game theory. She is a Simons Investigator, an ACM Fellow, a Sloan Fellow, a Microsoft Research New Faculty Fellow, and the recipient of the ACM Grace Murray Hopper Award, NSF CAREER award, and several best paper awards. </span></font>She has given distinguished lectures and invited keynote talks across different research fields (including machine learning, information theory, mathematics, and algorithmic game theory). <font face="arial, sans-serif"><span style="color:rgb(51,51,51)"> She has co-chaired major conferences in the field: the Conference on Learning Theory (COLT) 2014, the International Conference on Machine Learning (ICML) 2016, and Neural Information Processing Systems (NeurIPS) 2020. She was also the general chair for the International Conference on Machine Learning (ICML) 2021, a board member of the International Machine Learning Society, and a co-organizer for the Simo</span><span style="color:rgb(51,51,51)">ns semester on Foundations of Machine Learning.</span></font></div><div dir="ltr"><font face="arial, sans-serif"><span style="color:rgb(51,51,51)"><br></span></font></div><div><font face="arial, sans-serif"><span style="color:rgb(51,51,51)"><b>Host:</b> Avrim Blum</span></font></div><br class="gmail-Apple-interchange-newline"></div><div class="gmail_default" style="font-size:small"><br></div><div class="gmail_default" style="font-size:small"><br></div><div class="gmail_default" style="font-size:small"><br></div><div><div dir="ltr" class="gmail_signature"><div dir="ltr"><div><span style="font-family:arial,helvetica,sans-serif;font-size:x-small">Mary C. Marre</span><br></div><div><div><font face="arial, helvetica, sans-serif" size="1">Faculty Administrative Support</font></div><div><i><font face="arial, helvetica, sans-serif" color="#3d85c6" size="1"><b>Toyota Technological Institute</b></font></i></div><div><i><font face="arial, helvetica, sans-serif" color="#3d85c6" size="1">6045 S. Kenwood Avenue, Rm 517</font></i></div><div><font size="1"><i><font face="arial, helvetica, sans-serif" color="#3d85c6">Chicago, IL 60637</font></i><br></font></div><div><font size="1"><i><font face="arial, helvetica, sans-serif" color="#3d85c6">773-834-1757</font></i></font></div><div><b><i><a href="mailto:mmarre@ttic.edu" target="_blank"><font face="arial, helvetica, sans-serif" size="1">mmarre@ttic.edu</font></a></i></b></div></div></div></div></div><br></div><br><div class="gmail_quote"><div dir="ltr" class="gmail_attr">On Fri, Oct 25, 2024 at 1:35 PM Mary Marre <<a href="mailto:mmarre@ttic.edu">mmarre@ttic.edu</a>> wrote:<br></div><blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left:1px solid rgb(204,204,204);padding-left:1ex"><div dir="ltr"><div dir="ltr"><div style="font-size:small"><div><b>When</b>: Monday, October 28th from<b style="background-color:rgb(255,255,0)"> 11</b><b><span style="background-color:rgb(255,255,0)">am - 12pm CT</span></b></div><div><div><b><br></b></div><div><b>Where</b>: Talk will be given <b><font color="#0000ff">live, in-person</font></b> at<br> TTIC, 6045 S. Kenwood Avenue<br> 5th Floor, <b><u><font color="#000000">Room 530</font></u></b></div><div><br><b>Virtually</b>: <i><font color="#0000ff">tba</font></i><br></div><div> </div><div><b>Who: </b> Nina Balcan, Carnegie Mellon University</div><div><br></div></div><div><div style="border-top:none;border-right:none;border-left:none;border-bottom:2.25pt solid rgb(11,118,159);padding:0in 0in 1pt"></div><div><font face="arial, sans-serif"><b><br></b></font></div><div><div style="color:rgb(0,0,0);margin-top:0px;margin-bottom:0px"><span style="font-family:arial,sans-serif;color:rgb(51,51,51)"><b>Title: </b>Online learning in </span><span style="font-family:arial,sans-serif;color:rgb(51,51,51)">Stackelberg Security Games</span></div></div></div><div><span style="color:rgb(51,51,51)"><font face="arial, sans-serif"><br></font></span></div><div dir="ltr"><font face="arial, sans-serif"><span style="color:rgb(51,51,51)"><b>Abstract:</b> In a Stackelberg Security Game, a defender commits to a randomized deployment of security resources, and an attacker best responds by attacking a target that maximizes their utility. While algorithms for computing an optimal strategy for the defender to commit to have been used in several real-world applications, deployed applications require knowledge about the utility function of the potential attacker. In this talk I will describe an online learning approach for addressing this problem. We consider algorithms that prescribe a randomized strategy for the defender at each step against an adversarially chosen sequence of attackers and obtain feedback on their choices. I will discuss online algorithms whose regret (when compared to the best fixed strategy in hindsight) is sublinear in the number of time steps. I will also consider an extension that handles auxiliary contextual information that is often readily available to each player (e.g. traffic patterns or weather conditions) and discuss what no regret guarantees are possible in this even more realistic scenario.</span><br style="box-sizing:border-box;color:rgb(51,51,51)"><br style="box-sizing:border-box;color:rgb(51,51,51)"><strong style="box-sizing:border-box;margin:0px;padding:0px;border:0px;font-variant-numeric:inherit;font-variant-east-asian:inherit;font-variant-alternates:inherit;font-stretch:inherit;line-height:inherit;font-size-adjust:inherit;font-kerning:inherit;font-feature-settings:inherit;vertical-align:baseline;color:rgb(51,51,51)">Bio: </strong><span style="color:rgb(51,51,51)">Maria Florina Balcan is the Cadence Design Systems Professor of Computer Science in the School of Computer Science at Carnegie Mellon University. Her main research interests are machine learning, artificial intelligence, theory of computing, and algorithmic game theory. She is a Simons Investigator, an ACM Fellow, a Sloan Fellow, a Microsoft Research New Faculty Fellow, and the recipient of the ACM Grace Murray Hopper Award, NSF CAREER award, and several best paper awards. </span></font>She has given distinguished lectures and invited keynote talks across different research fields (including machine learning, information theory, mathematics, and algorithmic game theory). <font face="arial, sans-serif"><span style="color:rgb(51,51,51)"> She has co-chaired major conferences in the field: the Conference on Learning Theory (COLT) 2014, the International Conference on Machine Learning (ICML) 2016, and Neural Information Processing Systems (NeurIPS) 2020. She was also the general chair for the International Conference on Machine Learning (ICML) 2021, a board member of the International Machine Learning Society, and a co-organizer for the Simo</span><span style="color:rgb(51,51,51)">ns semester on Foundations of Machine Learning.</span></font></div><div dir="ltr"><font face="arial, sans-serif"><span style="color:rgb(51,51,51)"><br></span></font></div><div><font face="arial, sans-serif"><span style="color:rgb(51,51,51)"><b>Host:</b> Avrim Blum</span></font></div><div><font face="arial, sans-serif"><span style="color:rgb(51,51,51)"><br></span></font></div><div><font face="arial, sans-serif"><span style="color:rgb(51,51,51)"><br></span></font></div></div><div><div dir="ltr" class="gmail_signature"><div dir="ltr"><div><span style="font-family:arial,helvetica,sans-serif;font-size:x-small">Mary C. Marre</span><br></div><div><div><font face="arial, helvetica, sans-serif" size="1">Faculty Administrative Support</font></div><div><i><font face="arial, helvetica, sans-serif" color="#3d85c6" size="1"><b>Toyota Technological Institute</b></font></i></div><div><i><font face="arial, helvetica, sans-serif" color="#3d85c6" size="1">6045 S. Kenwood Avenue, Rm 517</font></i></div><div><font size="1"><i><font face="arial, helvetica, sans-serif" color="#3d85c6">Chicago, IL 60637</font></i><br></font></div><div><font size="1"><i><font face="arial, helvetica, sans-serif" color="#3d85c6">773-834-1757</font></i></font></div><div><b><i><a href="mailto:mmarre@ttic.edu" target="_blank"><font face="arial, helvetica, sans-serif" size="1">mmarre@ttic.edu</font></a></i></b></div></div></div></div></div></div>
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