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VERSION:2.0
PRODID:-//Memento EPFL//
BEGIN:VEVENT
SUMMARY:Proximal Envelopes
DTSTART:20151211T101500
DTEND:20151211T111500
DTSTAMP:20260407T183739Z
UID:8a7437716d7229aaaef5b3589b7fd5372b73f82f301cbccb8d5b0a07
CATEGORIES:Conferences - Seminars
DESCRIPTION:Panos Patrinos\nQuasi-Newton operator splitting methods for so
 lving nonsmooth optimization problems\nWe show that operator splitting tec
 hniques for solving optimization problems\, such as Forward-Backward Split
 ting (FBS)\, Douglas-Rachford Splitting (DRS) and ADMM\, can be interprete
 d as scaled gradient methods applied to the unconstrained minimization of 
 a continuously differentiable function. Inspired by the connection between
  the proximal minimization algorithm and the Moreau envelope\, we call the
 se functions Forward-Backward and Douglas-Rachford envelope. The new inter
 pretation paves the way of devising new algorithms for composite and separ
 able nonsmooth optimization problems\, by using ideas from Newton-like met
 hods for unconstrained smooth optimization.\nWe present applications of th
 e proposed theory:\nFirst\, a Forward-Backward Quasi-Newton method with as
 ymptotic superlinear convergence rate\, suitable for medium scale applicat
 ions like Model Predictive Control.\nSecond\, Forward-Backward L-BFGS algo
 rithms with complexity guarantees for large-scale nonsmooth optimization p
 roblems.\nFinally\, we derive complexity estimates for DRS and an accelera
 ted version of DRS and ADMM.\nBio: Panagiotis (Panos) Patrinos is currentl
 y an assistant professor at the Department of Electrical Engineering in KU
  Leuven. During fall/winter 2014 he held a visiting professor position in 
 the department of electrical engineering at Stanford University. He receiv
 ed his Ph.D. in Control and Optimization\, M.Sc. in Applied Mathematics an
 d M.Eng.\, all from National Technical University of Athens. After receivi
 ng his PhD he was a postdoctoral fellow at the University of Trento. In sp
 ring 2012 he became an assistant professor at IMT Institute for Advanced S
 tudies Lucca\, Italy. \nHe is the author of more than 40 papers in journa
 ls and refereed conference proceedings.His current research interests are 
 focused on efficient algorithms and modeling environments for large-scale 
 distributed and embedded optimization with applications in control of dyna
 mical systems\, high-dimensional statistics\, machine learning and data mi
 ning. He is also interested in stochastic and risk-averse optimization wit
 h applications in the energy and power systems domain.
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STATUS:CONFIRMED
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