\u65e5\u6642\uff1a\u30002017\u5e742\u670816\u65e5(\u6728) 14:00\uff5e15:00
\n\u5834\u6240\uff1a\u3000\u6771\u4eac\u5927\u5b66\u5de5\u5b66\u90e8 14\u53f7\u9928 5\u968e 534\u53f7\u5ba4
\nhttp:\/\/www.u-tokyo.ac.jp\/campusmap\/cam01_04_15_j.html<\/p>\n
\u8b1b\u6f14\u8005\uff1a Kim Chuan TOH \uff08National University of Singapore\uff09
\nhttp:\/\/www.math.nus.edu.sg\/~mattohkc\/<\/p>\n
\u8b1b\u6f14\u984c\u76ee\uff1a A two-phase augmented Lagrangian approach for
\nlinear and convex quadratic semidefinite programming problems<\/p>\n
\u8b1b\u6f14\u6982\u8981\uff1aWe consider the important class of high
\ndimensional linear and quadratic SDP problems with large
\nnumbers of linear equality and\/or inequality constraints. In
\nthis talk, we first introduce a symmetric Gauss-Seidel (sGS)
\ndecomposition theorem for solving an unconstrained convex
\ncomposite programming problem whose objective is the sum of
\na multi-block quadratic function and a non-smooth function
\ninvolving only the first block. Then, based on the sGS
\ndecomposition theorem, we design a two phase proximal
\naugmented Lagrangian method to efficiently solve the
\ntargeted problem to high accuracy. Specifically, in Phase I,
\nwe design an inexact sGS-based semi-proximal ADMM to
\ngenerate a reasonably good initial point to warm-start the
\nalgorithm in Phase II, which is a semi-smooth Newton-CG
\nbased proximal augmented Lagrangian method capable of
\ncomputing a high accuracy solution efficiently under certain
\nnondegeneracy conditions.
\nWe have developed a solver called SDPNAL+ based on the
\n2-phase algorithm for solving large scale linear SDP problems.
\nNumerous problems arising from combinatorial optimization
\nand binary integer quadratic programming problems have been
\ntested to evaluate the performance of the solver. Extensive
\nnumerical test results show that the proposed method is
\nquite efficient and robust.<\/p>\n","protected":false},"excerpt":{"rendered":"
\u65e5\u6642\uff1a\u30002017\u5e742\u670816\u65e5(\u6728) 14:00\uff5e15:00 \u5834\u6240\uff1a\u3000\u6771\u4eac\u5927\u5b66\u5de5\u5b66\u90e8 14\u53f7\u9928 5\u968e … <\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[3],"tags":[],"class_list":["post-293","post","type-post","status-publish","format-standard","hentry","category-3"],"_links":{"self":[{"href":"https:\/\/www.opt.mist.i.u-tokyo.ac.jp\/crest-model\/wp-json\/wp\/v2\/posts\/293","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.opt.mist.i.u-tokyo.ac.jp\/crest-model\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.opt.mist.i.u-tokyo.ac.jp\/crest-model\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.opt.mist.i.u-tokyo.ac.jp\/crest-model\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.opt.mist.i.u-tokyo.ac.jp\/crest-model\/wp-json\/wp\/v2\/comments?post=293"}],"version-history":[{"count":0,"href":"https:\/\/www.opt.mist.i.u-tokyo.ac.jp\/crest-model\/wp-json\/wp\/v2\/posts\/293\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.opt.mist.i.u-tokyo.ac.jp\/crest-model\/wp-json\/wp\/v2\/media?parent=293"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.opt.mist.i.u-tokyo.ac.jp\/crest-model\/wp-json\/wp\/v2\/categories?post=293"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.opt.mist.i.u-tokyo.ac.jp\/crest-model\/wp-json\/wp\/v2\/tags?post=293"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}