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As part of the Isaac Newton Institute research programme “Scalable Inference; Statistical, Algorithmic, Computional Aspects” to be held in July 2017, the workshop "Scalable statistical inference workshop" will be held 3rd July 2017 to 7th July 2017 at the Isaac Newton Institute, Cambridge (UK) The deadline for applications is 17th April 2017. For more detail on how to participate, please follow the link https://www.newton.ac.uk/event/sinw01 <https://www.newton.ac.uk/event/sinw01> More details about the research programme can be found at https://www.newton.ac.uk/event/sin <https://www.newton.ac.uk/event/sin> ==================================================================================================== Workshop Theme The complexity and sheer size of modern data sets, of which ever increasingly demanding questions are posed, give rise to major challenges and opportunities for modern statistics. Many of those challenges are of a computational nature and the aim of the workshop is to bring together researchers from a broad range of horizons with an interest in such issues, in particular scalability. Speakers currently include • Jose Blanchet (Columbia University) • Alexandre Bouchard (University of British Columbia) • Tamara Broderick (Massachusetts Institute of Technology) • Arnaud Doucet (University of Oxford) • Peter Glynn (Stanford University) • Katherine Heller (Duke University) • Michael Jordan (University of California, Berkeley) • Anthony Lee (University of Warwick) • Po-Ling Loh (University of Wisconsin-Madison) • Eric Moulines (Télécom ParisTech) • Sylvia Richardson (University of Cambridge) • Christian Robert (CNRS & Université Paris-Dauphine) • Havard Rue (King Abdullah University of Science and Technology (KAUST)) • James Scott (University of Texas at Austin) • Steve Scott (Google) • Cristiano Varin (Università Cà Foscari di Venezia) • Matti Vihola (University of Jyväskylä) • Helen Zhang (University of Arizona) Christophe - Prof. Christophe ANDRIEU tel: +44 (0)117 928 9134 School of Mathematics fax: +44 (0)117 928 7999 University of Bristol Bristol BS8 1TW, UK http://www.stats.bris.ac.uk/~maxca <http://www.stats.bris.ac.uk/~maxca> You may leave the list at any time by sending the command SIGNOFF allstat to [log in to unmask], leaving the subject line blank.