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X-WR-CALDESC:Events for IFDS
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DTSTART:20220313T100000
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DTSTART:20221106T090000
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20220107T123000
DTEND;TZID=America/Los_Angeles:20220107T133000
DTSTAMP:20260515T233502
CREATED:20220325T200214Z
LAST-MODIFIED:20220325T200231Z
UID:1927-1641558600-1641562200@ifds.info
SUMMARY:IFDS Monthly All-Hands: Sebastien Roch
DESCRIPTION:Speaker: Prof. Sebastien Roch\, UW-Madison\, Department of Mathematics   \nTitle: Phylogenomics: “Inverting” Random Trees   \nAbstract: The estimation of species phylogenies from genome-scale data is an important step in modern evolutionary studies. This estimation is complicated by the fact that genes evolve under biological processes that produce discordant trees. Such processes include horizontal gene transfer\, incomplete lineage sorting\, and gene duplication and loss\, all of which can be modeled using certain random tree distributions. I will discuss recent results on the identifiability\, or “invertibility”\, of these probabilistic models. I will also consider the large-sample properties of species tree estimation methods in this context. Based partly on joint works with Max Bacharach\, Brandon Legried\, Erin Molloy\, Elchanan Mossel\, Allan Sly\, Tandy Warnow\, Shuqi Yu.    
URL:https://ifds.info/event/ifds-monthly-all-hands-sebastien-roch/
LOCATION:WI
CATEGORIES:Monthly All-Hands
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Chicago:20220107T153000
DTEND;TZID=America/Chicago:20220107T163000
DTSTAMP:20260515T233502
CREATED:20220106T152210Z
LAST-MODIFIED:20220130T024429Z
UID:1739-1641569400-1641573000@ifds.info
SUMMARY:IFDS All-Hands: Sébastien Roche
DESCRIPTION:Title: Phylogenomics: “Inverting” Random Trees\n\nSpeaker: Sebastien Roch\, UW-Madison\, Department of Mathematics\n\nAbstract: The estimation of species phylogenies from genome-scale data is an important step in modern evolutionary studies. This estimation is complicated by the fact that genes evolve under biological processes that produce discordant trees. Such processes include horizontal gene transfer\, incomplete lineage sorting\, and gene duplication and loss\, all of which can be modeled using certain random tree distributions. I will discuss recent results on the identifiability\, or “invertibility”\, of these probabilistic models. I will also consider the large-sample properties of species tree estimation methods in this context. Based partly on joint works with Max Bacharach\, Brandon Legried\, Erin Molloy\, Elchanan Mossel\, Allan Sly\, Tandy Warnow\, Shuqi Yu.  \n\nBio: Sebastien Roch is a Professor in the Department of Mathematics at University of Wisconsin-Madison\, where he is also affiliated with the Department of Statistics and the Theory of Computing. He earned his Ph.D. in Statistics from the University of California\, Berkeley under the guidance of Elchanan Mossel. From 2007-2009\, he was a Postdoctoral Researcher at Microsoft Research. From 2009-2012\, he was a tenure-track Assistant Professor in the Department of Mathematics at the University of California-Los Angeles. He is the recipient of an NSF CAREER Award and of an Alfred P. Sloan Fellowship. He was a Kavli Fellow of the National Academy of Sciences in 2014 and 2017\, and was a 2018 Simons Fellow. He also received the Best Paper Award at RECOMB 2018. His research interests lie at the interface of applied probability\, statistics\, and theoretical computer science with an emphasis on biological applications.
URL:https://ifds.info/event/ifds-all-hands-sebastien-roche/
LOCATION:Zoom
CATEGORIES:Monthly All-Hands
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20220114T123000
DTEND;TZID=America/Los_Angeles:20220114T133000
DTSTAMP:20260515T233502
CREATED:20220325T200020Z
LAST-MODIFIED:20220325T200040Z
UID:1923-1642163400-1642167000@ifds.info
SUMMARY:ML Opt@ UW: Yue Sun
DESCRIPTION:Speaker: Yue Sun   \nTitle: Analysis of Policy Gradient Descent for Control: Global Optimality via Convex Parameterization   \nAbstract: Policy gradient descent is a popular approach in reinforcement learning due to its simplicity. Recent work has investigated the optimality and convergence properties of this method when applied in certain control problems. In this work\, we connect policy gradient descent (applied to a nonconvex problem formulation) with classical convex parameterizations in control theory\, to show the gradient dominance property for the nonconvex cost function. Such a connection between nonconvex and convex landscapes holds for continuous/discrete time LQR\, distributed optimal control\, minimizing the $cL_2$ gain\, among others. To the best of our knowledge\, this work offers the first result unifying the landscape analysis of a broad class of control problems.
URL:https://ifds.info/event/ml-opt-uw-yue-sun/
LOCATION:WI
CATEGORIES:MLOpt@UWash
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20220119T120000
DTEND;TZID=America/Los_Angeles:20220119T130000
DTSTAMP:20260515T233502
CREATED:20210921T203152Z
LAST-MODIFIED:20210921T203341Z
UID:1684-1642593600-1642597200@ifds.info
SUMMARY:E & A SIG:
DESCRIPTION:
URL:https://ifds.info/event/e-a-sig-4/
LOCATION:WI
CATEGORIES:E & A SIG
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Chicago:20220121T123000
DTEND;TZID=America/Chicago:20220121T133000
DTSTAMP:20260515T233502
CREATED:20220325T195836Z
LAST-MODIFIED:20220325T195856Z
UID:1919-1642768200-1642771800@ifds.info
SUMMARY:ML Opt@ UW: Lang Liu
DESCRIPTION:Speaker: Lang Liu \nTitle: The Sample Complexity of Statistical Comparison Between Generative Models \nAbstract: The spectacular success of deep generative models calls for quantitative tools to measure their statistical performance. Divergence frontiers have recently been proposed as an evaluation framework for generative models. Although practically successful\, the sample complexity of the empirical estimator of divergence frontiers is unknown. We establish non-asymptotic bounds on the sample complexity of divergence frontiers\, providing theoretical guidance on their estimation procedure.
URL:https://ifds.info/event/ml-opt-uw-lang-liu/
LOCATION:WI
CATEGORIES:MLOpt@UWash
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Chicago:20220126T123000
DTEND;TZID=America/Chicago:20220126T133000
DTSTAMP:20260515T233502
CREATED:20220119T204000Z
LAST-MODIFIED:20220119T204011Z
UID:1804-1643200200-1643203800@ifds.info
SUMMARY:SILO: Csaba Szepesvari
DESCRIPTION:
URL:https://ifds.info/event/silo-csaba-szepesvari/
LOCATION:Orchard View Room\, 330 N. Orchard Street\, 3rd Floor NE\, Madison\, Wisconsin\, 53715\, United States
CATEGORIES:SILO
ORGANIZER;CN="Rob%20Nowak":MAILTO:rdnowak@wisc.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Chicago:20220131T123000
DTEND;TZID=America/Chicago:20220131T133000
DTSTAMP:20260515T233502
CREATED:20220119T200612Z
LAST-MODIFIED:20220119T200918Z
UID:1753-1643632200-1643635800@ifds.info
SUMMARY:IFDS Ideas Forum
DESCRIPTION:
URL:https://ifds.info/event/ifds-ideas-forum/
LOCATION:Orchard View Room\, 330 N. Orchard Street\, 3rd Floor NE\, Madison\, Wisconsin\, 53715\, United States
CATEGORIES:IFDS Ideas Forum
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Chicago:20220131T140000
DTEND;TZID=America/Chicago:20220131T140000
DTSTAMP:20260515T233502
CREATED:20230313T142147Z
LAST-MODIFIED:20230313T142147Z
UID:2425-1643637600-1643637600@ifds.info
SUMMARY:IFDS Ideas Forum
DESCRIPTION:Lightning talks for ICML+COLT submissions
URL:https://ifds.info/event/ifds-ideas-forum-5/
LOCATION:WI
END:VEVENT
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