BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Memento EPFL//
BEGIN:VEVENT
SUMMARY:Gradient Based Optimization Algorithms
DTSTART:20140204T111500
DTEND:20140204T121500
DTSTAMP:20260407T102523Z
UID:324d7026b7a92c51465c97deb06e07e109e4e3cb339fe8ccbf43d302
CATEGORIES:Conferences - Seminars
DESCRIPTION:Prof. Marc Teboulle\, Tel-Aviv University\nBio: Marc Teboulle 
 is a Professor at the School of Mathematical Sciences of Tel-Aviv Universi
 ty. He received his D.Sc. from the Technion\, Israel Institute of Technolo
 gy in 1985. He has held a position of applied mathematician at the Israel 
 Aircraft Industries\, and academic appointements at Dalhousie University a
 nd the University of Maryland. He has also held visiting appointments at s
 everal institutions\, including IMPA (Rio de Janeiro)\, the University of 
 Montpellier\, the University of Paris\, University of Lyon\, the Universit
 y of Michigan\, the University of Texas at Austin\, The National Sun Yat-s
 en University\, Kaohsiung\, Taiwan\, Republic of China\, and The Universit
 y of California\, Los Angeles.\nTeboulle research interests are in the are
 a of continuous optimization\, including theory\, algorithmic analysis and
  its applications. He has published numerous papers and two books\, and ha
 s given invited lectures at many international conferences. His research h
 as been supported by various funding agencies including\, the National Sci
 ence Foundation\, the French-Israeli Ministry of Sciences\, the Bi-Nationa
 l Israel-United States Science Foundation\, and the Israel Science Foundat
 ion. He currently serves as the Area Editor for Continuous Optimization of
  Mathematics of Operations Research\; and on the editorial boards of the E
 uropean Series in Applied and Industrial Mathematics\, Control\, Optimisat
 ion and Calculus of Variations\, Journal of Optimization Theory and Applic
 ations\, and Science China Mathematics. During 1999-2002\, he served as ch
 airman of the Department of Statistics and Operations Research at the Scho
 ol of Mathematical Sciences of Tel-Aviv University.\nOptimization methods 
 applied to problems in image processing\, machine learning and other field
 s give rise to very large scale\, often nonsmooth and even nonconvex optim
 ization models. This leads to challenging theoretical and computational di
 fficulties which rule out the use of most of the sophisticated algorithms\
 , such as interior point\,  since the number of arithmetic operations req
 uired in a single iteration is already prohibitively large. Elementary fir
 st order methods (using function values and gradient/subgradient informati
 on) then often remain our best alternative to tackle such problems.\nThis 
 talk surveys some of our recent results on the design and analysis of firs
 t-order algorithms for various generic optimization models arising in a wi
 de variety of applications\, highlighting the ways in which problem struct
 ures and data information can be beneficially exploited to devise simple a
 nd efficient algorithms.
LOCATION:EPFL MXF1 http://plan.epfl.ch/?zoom=21&recenter_y=5863946.21509&r
 ecenter_x=730658.04689&layerNodes=fonds\,batiments\,labels\,information\,p
 arkings_publics\,arrets_metro\,transports_publics&q=mxf1
STATUS:CONFIRMED
END:VEVENT
END:VCALENDAR