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  • Feb
    18

    IEMS Seminar: Piecewise deterministic Markov processes for MCMC - A large deviations analysis of the zig-zag sampler

    Department of Industrial Engineering and Management Sciences

    11:00 AM M228, Technological Institute

    EVENT DETAILS

    Pierre Nyquist

    KTH Royal Institute of Technology

    Title: Piecewise deterministic Markov processes for MCMC - A large deviations analysis of the zig-zag sampler

    Abstract:

    Over the last decade piecewise deterministic Markov processes (PDMPs) have emerged as a new tool for MCMC simulation, potentially mitigating the problems of slow convergence and heavy computational cost exhibited by many other methods. The two main examples of such processes are the bouncy particle sampler and the zig-zag sampler. The idea of using PDMPs extends the ubiquitous discrete time MCMC methodology towards a new continuous time approach, having several advantageous aspects, for example non-reversibility and the possibility to reduce the computational effort per iteration by using subsampling techniques.

    In order to employ this new PDMP methodology a solid understanding of mathematical properties of these methods is necessary. Whereas the theoretical
    properties of PDMPs have been an active research area in recent years, our understanding of the performance of the corresponding MCMC methods is still incomplete. In particular knowledge of the speed of convergence of time averages is essential in choosing the most suitable sampling technology for a particular problem and in tuning the parameters of the chosen method.

    In this talk I will discuss recent work on using large deviation results for empirical measures to study and compare the performance of PDMPs. We will start with a general discussion of non-reversible MCMC methods and the use of empirical measure large deviations in the simulation setting. We then focus on PDMPs, in particular the zig-zag sampler, and a large deviations analysis based on the Feng-Krutz approach; no previous knowledge of either PDMPs or large deviations will be necessary. This is based on joint work with Joris Bierkens and Mikola Schlottke.

    Bio:

    Pierre Nyquist is associate professor in the Department of Mathematics at KTH Royal Institute of Technology in Stockholm. He received his PhD in Applied and Computational Mathematics from the same institution in 2014. Before moving back to KTH in 2018 he spent time as a postdoc in the Division of Applied Mathematics at Brown University and as assistant professor at Eindhoven University of Technology. His research interests lie broadly at the intersection of analysis and probability and include large deviations, stochastic control, interacting particle systems and design and analysis of Monte Carlo methods. Recent work has focused on the mathematical foundation of methods in machine learning.

    Title: Piecewise deterministic Markov processes for MCMC - A large deviations analysis of the zig-zag sampler

    Abstract:

    Over the last decade piecewise deterministic Markov processes (PDMPs) have emerged as a new tool for MCMC simulation, potentially mitigating the problems of slow convergence and heavy computational cost exhibited by many other methods. The two main examples of such processes are the bouncy particle sampler and the zig-zag sampler. The idea of using PDMPs extends the ubiquitous discrete time MCMC methodology towards a new continuous time approach, having several advantageous aspects, for example non-reversibility and the possibility to reduce the computational effort per iteration by using subsampling techniques.

    In order to employ this new PDMP methodology a solid understanding of mathematical properties of these methods is necessary. Whereas the theoretical
    properties of PDMPs have been an active research area in recent years, our understanding of the performance of the corresponding MCMC methods is still incomplete. In particular knowledge of the speed of convergence of time averages is essential in choosing the most suitable sampling technology for a particular problem and in tuning the parameters of the chosen method.

    In this talk I will discuss recent work on using large deviation results for empirical measures to study and compare the performance of PDMPs. We will start with a general discussion of non-reversible MCMC methods and the use of empirical measure large deviations in the simulation setting. We then focus on PDMPs, in particular the zig-zag sampler, and a large deviations analysis based on the Feng-Krutz approach; no previous knowledge of either PDMPs or large deviations will be necessary. This is based on joint work with Joris Bierkens and Mikola Schlottke.

    Bio:

    Pierre Nyquist is associate professor in the Department of Mathematics at KTH Royal Institute of Technology in Stockholm. He received his PhD in Applied and Computational Mathematics from the same institution in 2014. Before moving back to KTH in 2018 he spent time as a postdoc in the Division of Applied Mathematics at Brown University and as assistant professor at Eindhoven University of Technology. His research interests lie broadly at the intersection of analysis and probability and include large deviations, stochastic control, interacting particle systems and design and analysis of Monte Carlo methods. Recent work has focused on the mathematical foundation of methods in machine learning.

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    TIME Tuesday, February 18, 2020 at 11:00 AM - 12:00 PM

    LOCATION M228, Technological Institute    map it

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    CONTACT Agnes Kaminski    a-kaminski@northwestern.edu EMAIL

    CALENDAR Department of Industrial Engineering and Management Sciences

  • Mar
    14

    Winter Classes End

    University Academic Calendar

    All Day

    EVENT DETAILS

    TIME Saturday, March 14, 2020

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    CONTACT Office of the Registrar    nu-registrar@northwestern.edu EMAIL

    CALENDAR University Academic Calendar

  • Mar
    21

    Spring Break Begins

    University Academic Calendar

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    EVENT DETAILS

    TIME Saturday, March 21, 2020

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    CONTACT Office of the Registrar    nu-registrar@northwestern.edu EMAIL

    CALENDAR University Academic Calendar

  • Mar
    30

    Spring Break Ends

    University Academic Calendar

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    EVENT DETAILS

    TIME Monday, March 30, 2020

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    CONTACT Office of the Registrar    nu-registrar@northwestern.edu EMAIL

    CALENDAR University Academic Calendar

  • Mar
    31

    Spring Classes Begin 8 a.m. - Note: Northwestern Monday - Monday classes

    University Academic Calendar

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    EVENT DETAILS

    TIME Tuesday, March 31, 2020

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    CONTACT Office of the Registrar    nu-registrar@northwestern.edu EMAIL

    CALENDAR University Academic Calendar

  • May
    25

    Memorial Day (no classes)

    University Academic Calendar

    All Day

    EVENT DETAILS

    TIME Monday, May 25, 2020

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    CONTACT Office of the Registrar    nu-registrar@northwestern.edu EMAIL

    CALENDAR University Academic Calendar

  • Jun
    6

    Spring classes end

    University Academic Calendar

    All Day

    EVENT DETAILS

    TIME Saturday, June 6, 2020

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    CONTACT Office of the Registrar    nu-registrar@northwestern.edu EMAIL

    CALENDAR University Academic Calendar

  • Jun
    19

    McCormick PhD Hooding Ceremony

    McCormick School of Engineering and Applied Science

    2:00 PM Ryan Family Auditorium, Technological Institute

    EVENT DETAILS

    TIME Friday, June 19, 2020 at 2:00 PM - 3:30 PM

    LOCATION Ryan Family Auditorium, Technological Institute    map it

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    CONTACT Northwestern Engineering Events    northwestern-engineering-events@northwestern.edu EMAIL

    CALENDAR McCormick School of Engineering and Applied Science

  • Jun
    20

    McCormick Undergraduate Convocation

    McCormick School of Engineering and Applied Science

    8:30 AM McGaw Memorial Hall/Welsh-Ryan Arena

    EVENT DETAILS

    TIME Saturday, June 20, 2020 at 8:30 AM - 10:00 AM

    LOCATION McGaw Memorial Hall/Welsh-Ryan Arena    map it

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    CONTACT Northwestern Engineering Events    northwestern-engineering-events@northwestern.edu EMAIL

    CALENDAR McCormick School of Engineering and Applied Science

  • Jun
    20

    McCormick Master's Recognition Ceremony

    McCormick School of Engineering and Applied Science

    12:30 PM McGaw Memorial Hall/Welsh-Ryan Arena

    EVENT DETAILS

    TIME Saturday, June 20, 2020 at 12:30 PM - 2:30 PM

    LOCATION McGaw Memorial Hall/Welsh-Ryan Arena    map it

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    CONTACT Northwestern Engineering Events    northwestern-engineering-events@northwestern.edu EMAIL

    CALENDAR McCormick School of Engineering and Applied Science