untitled
<OAI-PMH schemaLocation=http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd> <responseDate>2018-01-15T18:37:54Z</responseDate> <request identifier=oai:HAL:hal-00761657v1 verb=GetRecord metadataPrefix=oai_dc>http://api.archives-ouvertes.fr/oai/hal/</request> <GetRecord> <record> <header> <identifier>oai:HAL:hal-00761657v1</identifier> <datestamp>2017-12-21</datestamp> <setSpec>type:ART</setSpec> <setSpec>subject:math</setSpec> <setSpec>collection:INSMI</setSpec> <setSpec>collection:BNRMI</setSpec> <setSpec>collection:UNIV-AG</setSpec> <setSpec>collection:TDS-MACS</setSpec> </header> <metadata><dc> <publisher>HAL CCSD</publisher> <title lang=en>Extended Forward-Backward Algorithm</title> <creator>Lassonde, Marc</creator> <creator>Nagesseur, Ludovic</creator> <contributor>Laboratoire de Mathématiques Informatique et Applications (LAMIA) ; Université des Antilles et de la Guyane (UAG)</contributor> <description>International audience</description> <source>Journal of Mathematical Analysis and applications</source> <publisher>Elsevier</publisher> <identifier>hal-00761657</identifier> <identifier>https://hal.archives-ouvertes.fr/hal-00761657</identifier> <source>https://hal.archives-ouvertes.fr/hal-00761657</source> <source>Journal of Mathematical Analysis and applications, Elsevier, 2013, 403 (1), pp.167-172. 〈10.1016/j.jmaa.2013.02.022〉</source> <identifier>ARXIV : 1212.0523</identifier> <relation>info:eu-repo/semantics/altIdentifier/arxiv/1212.0523</relation> <identifier>DOI : 10.1016/j.jmaa.2013.02.022</identifier> <relation>info:eu-repo/semantics/altIdentifier/doi/10.1016/j.jmaa.2013.02.022</relation> <language>en</language> <subject>[MATH.MATH-OC] Mathematics [math]/Optimization and Control [math.OC]</subject> <type>info:eu-repo/semantics/article</type> <type>Journal articles</type> <description lang=en>We propose an extended forward-backward algorithm for approximating a zero of a maximal monotone operator which can be split as the extended sum of two maximal monotone operators. We establish the weak convergence in average of the sequence generated by the algorithm under assumptions similar to those used in classical forward-backward algorithms. This provides as a special case an algorithm for solving convex constrained minimization problems without qualification condition.</description> <date>2013-07-01</date> </dc> </metadata> </record> </GetRecord> </OAI-PMH>