<div dir="ltr">Please note this virtual talk series, which looks to be pretty interesting.<div><br></div><div>Best,</div><div><br></div><div>Mike<br><br><div class="gmail_quote"><div dir="ltr" class="gmail_attr">---------- Forwarded message ---------<br>From: <strong class="gmail_sendername" dir="auto">C3.ai Digital Transformation Institute</strong> <span dir="auto"><<a href="mailto:info@c3dti.ai">info@c3dti.ai</a>></span><br>Date: Mon, Feb 14, 2022 at 8:59 AM<br>Subject: Michael Jordan on Dynamics-Informed Blending of Machine Learning and Game Theory<br>To: <<a href="mailto:mjfranklin@uchicago.edu">mjfranklin@uchicago.edu</a>><br></div><br><br><u></u>
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<span class="m_-3241676250342574345mcnPreviewText" style="display:none;font-size:0px;line-height:0px;max-height:0px;max-width:0px;opacity:0;overflow:hidden">Michael Jordan on Dynamics-Informed Blending of Machine Learning and Game Theory</span>
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<div style="text-align:center">The Colloquium on Digital Transformation is a series of weekly online talks on how artificial intelligence, machine learning, and big data can lead to scientific breakthroughs with large-scale societal benefit.</div>
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<h1 style="text-align:center;display:block;margin:0;padding:0;color:#202020;font-family:Arial,'Helvetica Neue',Helvetica,sans-serif;font-size:26px;font-style:normal;font-weight:bold;line-height:125%;letter-spacing:normal"><strong>On Dynamics-Informed Blending of<br>
Machine Learning and Game Theory</strong></h1>
<p style="text-align:center;font-style:normal;font-weight:normal;margin:10px 0;padding:0;color:#202020;font-family:Helvetica;font-size:16px;line-height:150%"><strong><span style="font-size:16px">February 17, 1 pm PT/3 pm CT</span></strong><br>
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<strong>Michael I. Jordan, Pehong Chen Distinguished Professor<br>
University of California, Berkeley</strong><br>
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<a href="https://c3dti.us8.list-manage.com/track/click?u=aae4610086c8b3a8646b00cbe&id=30dc5aea82&e=f368f1abe4" style="color:#007c89;font-weight:normal;text-decoration:none" target="_blank"><img height="79" src="https://mcusercontent.com/aae4610086c8b3a8646b00cbe/images/35022080-a7ad-4881-8ff3-7ebb14f1b54f.png" style="border:0px;width:179px;height:79px;margin:0px;outline:none;text-decoration:none" width="179"></a></p>
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<p dir="ltr" style="text-align:justify;margin:10px 0;padding:0;color:#202020;font-family:Helvetica;font-size:16px;line-height:150%">Much of the recent focus in machine learning has been on the pattern-recognition side of the field. I will focus instead on the decision-making side, where many fundamental challenges remain. Some are statistical in nature, including the challenges associated with multiple decision-making, and some are algorithmic — including the challenge of coordinated decision-making on distributed platforms, and others are economic, involving learning systems that must cope with scarcity, competition, and incentives. I will present recent progress on each of these fronts, focusing on the economics front.<br>
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<a href="https://c3dti.us8.list-manage.com/track/click?u=aae4610086c8b3a8646b00cbe&id=1f721acbcc&e=f368f1abe4" style="color:#007c89;font-weight:normal;text-decoration:none" target="_blank">Michael I. Jordan</a> is the Pehong Chen Distinguished Professor at the University of California, Berkeley. His research interests include machine learning, optimization, control theory, and computational biology. Professor Jordan is a member of the National Academy of Sciences, the National Academy of Engineering, and the American Academy of Arts and Sciences. He is a Foreign Member of the Royal Society. He was a Plenary Lecturer at the International Congress of Mathematicians in 2018. He has received the Ulf Grenander Prize from the American Mathematical Society, the IEEE John von Neumann Medal, the IJCAI Research Excellence Award, the David Rumelhart Prize, and the ACM/AAAI Allen Newell Award.</p>
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<div style="text-align:left">February 24, 1 pm PT/3 pm CT<br>
<strong>David Shmoys</strong>, Laibe/Acheson Professor, Cornell University<br>
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March 3, 1 pm PT/3 pm CT<br>
<strong>Asuman Ozdaglar</strong>, MathWorks Professor of Electrical Engineering and Computer Science; Department Head, EECS, Massachusetts Institute of Technology<br>
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March 10, 1 pm PT/3 pm CT<br>
<strong>Christos Papadimitriou</strong>, Donovan Family Professor of Computer Science, Columbia University<br>
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<strong><span style="font-size:18px">Watch all C3.ai DTI talks on<br>
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<div style="text-align:center"><em>The Science of Digital Transformation</em><br>
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<div style="text-align:center"><span style="font-size:13px"><span style="font-family:arial,helvetica neue,helvetica,sans-serif"><strong>About the C3.ai Digital Transformation Institute</strong></span></span><br>
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<div style="text-align:justify"><span style="font-size:12px"><span style="font-family:arial,helvetica neue,helvetica,sans-serif">Established in March 2020 by C3 AI, Microsoft, and leading universities, the C3.ai Digital Transformation Institute is a research consortium dedicated to accelerating the socioeconomic benefits of artificial intelligence. The Institute engages the world’s leading scientists to conduct research and train practitioners in the new Science of Digital Transformation, which operates at the intersection of artificial intelligence, machine learning, cloud computing, internet of things, big data analytics, organizational behavior, public policy, and ethics. The ten C3.ai Digital Transformation Institute consortium member universities and research laboratories are: University of Illinois at Urbana-Champaign; University of California, Berkeley; Carnegie Mellon University; KTH Royal Institute of Technology; Lawrence Berkeley National Laboratory; Massachusetts Institute of Technology; National Center for Supercomputing Applications at University of Illinois at Urbana-Champaign; Princeton University; Stanford University; and University of Chicago. Learn more at <a href="https://c3dti.us8.list-manage.com/track/click?u=aae4610086c8b3a8646b00cbe&id=6ac351bc26&e=f368f1abe4" style="color:#007c89;font-weight:normal;text-decoration:none" target="_blank">C3DTI.ai</a>.</span></span></div>
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