<?xml version="1.0" encoding="utf-8"?>
<TEI xmlns="http://www.tei-c.org/ns/1.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:hal="http://hal.archives-ouvertes.fr/" xmlns:gml="http://www.opengis.net/gml/3.3/" xmlns:gmlce="http://www.opengis.net/gml/3.3/ce" version="1.1" xsi:schemaLocation="http://www.tei-c.org/ns/1.0 http://api.archives-ouvertes.fr/documents/aofr-sword.xsd">
  <teiHeader>
    <fileDesc>
      <titleStmt>
        <title>HAL TEI export of hal-02114975</title>
      </titleStmt>
      <publicationStmt>
        <distributor>CCSD</distributor>
        <availability status="restricted">
          <licence target="https://creativecommons.org/publicdomain/zero/1.0/">CC0 1.0 - Universal</licence>
        </availability>
        <date when="2026-05-25T05:52:22+02:00"/>
      </publicationStmt>
      <sourceDesc>
        <p part="N">HAL API Platform</p>
      </sourceDesc>
    </fileDesc>
  </teiHeader>
  <text>
    <body>
      <listBibl>
        <biblFull>
          <titleStmt>
            <title xml:lang="en">Deep Multi-Wasserstein Unsupervised Domain Adaptation</title>
            <author role="aut">
              <persName>
                <forename type="first">Tien-Nam</forename>
                <surname>Le</surname>
              </persName>
              <email type="md5">8c967ccef9fd92b400187018de9c5289</email>
              <email type="domain">ens-lyon.fr</email>
              <idno type="idhal" notation="numeric">973747</idno>
              <idno type="halauthorid" notation="string">974487-973747</idno>
              <idno type="IDREF">https://www.idref.fr/234271698</idno>
              <idno type="VIAF">https://viaf.org/viaf/68157098562472552491</idno>
              <idno type="ORCID">https://orcid.org/0000-0002-1732-7988</idno>
              <affiliation ref="#struct-17835"/>
            </author>
            <author role="aut">
              <persName>
                <forename type="first">Amaury</forename>
                <surname>Habrard</surname>
              </persName>
              <email type="md5">953bfd7efd986cc4bed87a5dd35121e1</email>
              <email type="domain">univ-st-etienne.fr</email>
              <idno type="idhal" notation="string">amaury-habrard</idno>
              <idno type="idhal" notation="numeric">439</idno>
              <idno type="halauthorid" notation="string">13354-439</idno>
              <idno type="IDREF">https://www.idref.fr/084103655</idno>
              <idno type="ORCID">https://orcid.org/0000-0003-3038-9347</idno>
              <affiliation ref="#struct-17835"/>
            </author>
            <author role="aut">
              <persName>
                <forename type="first">Marc</forename>
                <surname>Sebban</surname>
              </persName>
              <email type="md5">b3e5e85bd0055d1799a5e06cad46eb80</email>
              <email type="domain">univ-st-etienne.fr</email>
              <idno type="idhal" notation="string">marc-sebban</idno>
              <idno type="idhal" notation="numeric">5203</idno>
              <idno type="halauthorid" notation="string">14963-5203</idno>
              <idno type="IDREF">https://www.idref.fr/050802623</idno>
              <idno type="ORCID">https://orcid.org/0000-0001-6851-169X</idno>
              <affiliation ref="#struct-17835"/>
            </author>
            <editor role="depositor">
              <persName>
                <forename>Marc</forename>
                <surname>Sebban</surname>
              </persName>
              <email type="md5">b3e5e85bd0055d1799a5e06cad46eb80</email>
              <email type="domain">univ-st-etienne.fr</email>
            </editor>
            <funder ref="#projanr-49679"/>
          </titleStmt>
          <editionStmt>
            <edition n="v1" type="current">
              <date type="whenSubmitted">2025-03-26 08:26:37</date>
              <date type="whenModified">2026-04-23 14:50:06</date>
              <date type="whenReleased">2025-03-26 11:46:34</date>
              <date type="whenProduced">2019-07-01</date>
              <date type="whenEndEmbargoed">2025-03-26</date>
              <ref type="file" target="https://hal.science/hal-02114975v1/document">
                <date notBefore="2025-03-26"/>
              </ref>
              <ref type="file" subtype="author" n="1" target="https://hal.science/hal-02114975v1/file/PRL2019.pdf" id="file-5005959-4337939">
                <date notBefore="2025-03-26"/>
              </ref>
            </edition>
            <respStmt>
              <resp>contributor</resp>
              <name key="112497">
                <persName>
                  <forename>Marc</forename>
                  <surname>Sebban</surname>
                </persName>
                <email type="md5">b3e5e85bd0055d1799a5e06cad46eb80</email>
                <email type="domain">univ-st-etienne.fr</email>
              </name>
            </respStmt>
          </editionStmt>
          <publicationStmt>
            <distributor>CCSD</distributor>
            <idno type="halId">hal-02114975</idno>
            <idno type="halUri">https://hal.science/hal-02114975</idno>
            <idno type="halBibtex">le:hal-02114975</idno>
            <idno type="halRefHtml">&lt;i&gt;Pattern Recognition Letters&lt;/i&gt;, 2019, 125, pp.249-255. &lt;a target="_blank" href="https://dx.doi.org/10.1016/j.patrec.2019.04.025"&gt;&amp;#x27E8;10.1016/j.patrec.2019.04.025&amp;#x27E9;&lt;/a&gt;</idno>
            <idno type="halRef">Pattern Recognition Letters, 2019, 125, pp.249-255. &amp;#x27E8;10.1016/j.patrec.2019.04.025&amp;#x27E9;</idno>
            <availability status="restricted">
              <licence target="https://creativecommons.org/licenses/by-nc-nd/4.0/">CC BY-NC-ND 4.0 - Attribution - Non-commercial use - No Derivative Works<ref corresp="#file-5005959-4337939"/></licence>
            </availability>
          </publicationStmt>
          <seriesStmt>
            <idno type="stamp" n="UNIV-ST-ETIENNE">Université Jean Monnet - Saint-Etienne</idno>
            <idno type="stamp" n="IOGS" corresp="PARISTECH">Institut d'Optique Graduate School</idno>
            <idno type="stamp" n="CNRS">CNRS - Centre national de la recherche scientifique</idno>
            <idno type="stamp" n="PARISTECH">ParisTech</idno>
            <idno type="stamp" n="UDL">UDL</idno>
            <idno type="stamp" n="ANR">ANR</idno>
            <idno type="stamp" n="LABORATOIRE-HUBERT-CURIEN" corresp="UNIV-ST-ETIENNE">LAboratoire Hubert Curien</idno>
          </seriesStmt>
          <notesStmt>
            <note type="audience" n="2">International</note>
            <note type="popular" n="0">No</note>
            <note type="peer" n="1">Yes</note>
          </notesStmt>
          <sourceDesc>
            <biblStruct>
              <analytic>
                <title xml:lang="en">Deep Multi-Wasserstein Unsupervised Domain Adaptation</title>
                <author role="aut">
                  <persName>
                    <forename type="first">Tien-Nam</forename>
                    <surname>Le</surname>
                  </persName>
                  <email type="md5">8c967ccef9fd92b400187018de9c5289</email>
                  <email type="domain">ens-lyon.fr</email>
                  <idno type="idhal" notation="numeric">973747</idno>
                  <idno type="halauthorid" notation="string">974487-973747</idno>
                  <idno type="IDREF">https://www.idref.fr/234271698</idno>
                  <idno type="VIAF">https://viaf.org/viaf/68157098562472552491</idno>
                  <idno type="ORCID">https://orcid.org/0000-0002-1732-7988</idno>
                  <affiliation ref="#struct-17835"/>
                </author>
                <author role="aut">
                  <persName>
                    <forename type="first">Amaury</forename>
                    <surname>Habrard</surname>
                  </persName>
                  <email type="md5">953bfd7efd986cc4bed87a5dd35121e1</email>
                  <email type="domain">univ-st-etienne.fr</email>
                  <idno type="idhal" notation="string">amaury-habrard</idno>
                  <idno type="idhal" notation="numeric">439</idno>
                  <idno type="halauthorid" notation="string">13354-439</idno>
                  <idno type="IDREF">https://www.idref.fr/084103655</idno>
                  <idno type="ORCID">https://orcid.org/0000-0003-3038-9347</idno>
                  <affiliation ref="#struct-17835"/>
                </author>
                <author role="aut">
                  <persName>
                    <forename type="first">Marc</forename>
                    <surname>Sebban</surname>
                  </persName>
                  <email type="md5">b3e5e85bd0055d1799a5e06cad46eb80</email>
                  <email type="domain">univ-st-etienne.fr</email>
                  <idno type="idhal" notation="string">marc-sebban</idno>
                  <idno type="idhal" notation="numeric">5203</idno>
                  <idno type="halauthorid" notation="string">14963-5203</idno>
                  <idno type="IDREF">https://www.idref.fr/050802623</idno>
                  <idno type="ORCID">https://orcid.org/0000-0001-6851-169X</idno>
                  <affiliation ref="#struct-17835"/>
                </author>
              </analytic>
              <monogr>
                <idno type="halJournalId" status="VALID">17800</idno>
                <idno type="issn">0167-8655</idno>
                <title level="j">Pattern Recognition Letters</title>
                <imprint>
                  <publisher>Elsevier</publisher>
                  <biblScope unit="volume">125</biblScope>
                  <biblScope unit="pp">249-255</biblScope>
                  <date type="datePub">2019-07-01</date>
                </imprint>
              </monogr>
              <idno type="doi">10.1016/j.patrec.2019.04.025</idno>
            </biblStruct>
          </sourceDesc>
          <profileDesc>
            <langUsage>
              <language ident="en">English</language>
            </langUsage>
            <textClass>
              <classCode scheme="halDomain" n="info.info-lg">Computer Science [cs]/Machine Learning [cs.LG]</classCode>
              <classCode scheme="halTypology" n="ART">Journal articles</classCode>
              <classCode scheme="halOldTypology" n="ART">Journal articles</classCode>
              <classCode scheme="halTreeTypology" n="ART">Journal articles</classCode>
            </textClass>
            <abstract xml:lang="en">
              <p>In unsupervised domain adaptation (DA), 1 aims at learning from labeled source data and fully unlabeled target examples a model with a low error on the target domain. In this setting, standard generalization bounds prompt us to minimize the sum of three terms: (a) the source true risk, (b) the divergence between the source and target domains, and (c) the combined error of the ideal joint hypothesis over the two domains. Many DA methods – especially those using deep neural networks – have focused on the first two terms by using different divergence measures to align the source and target distributions on a shared latent feature space, while ignoring the third term, assuming it is negligible to perform the adaptation. However, it has been shown that purely aligning the two distributions while minimizing the source error may lead to so-called negative transfer. In this paper, we address this issue with a new deep unsupervised DA method – called MCDA  – minimizing the first two terms while controlling the third one. MCDA benefits from highly-confident target samples (using softmax predictions) to minimize class-wise Wasserstein distances and efficiently approximate the ideal joint hypothesis. Empirical results show that our approach outperforms state of the art methods.</p>
            </abstract>
          </profileDesc>
        </biblFull>
      </listBibl>
    </body>
    <back>
      <listOrg type="structures">
        <org type="laboratory" xml:id="struct-17835" status="VALID">
          <idno type="IdRef">164609741</idno>
          <idno type="ISNI">0000 0000 9955 0977</idno>
          <idno type="RNSR">199511960B</idno>
          <idno type="ROR">https://ror.org/0028p8r67</idno>
          <orgName>Laboratoire Hubert Curien</orgName>
          <orgName type="acronym">LabHC</orgName>
          <date type="start">2006-01-01</date>
          <desc>
            <address>
              <addrLine>Bâtiment F 18 Rue du Professeur Benoît Lauras42000 Saint-Etienne</addrLine>
              <country key="FR"/>
            </address>
            <ref type="url">http://laboratoirehubertcurien.fr</ref>
          </desc>
          <listRelation>
            <relation active="#struct-300036" type="direct"/>
            <relation active="#struct-300284" type="direct"/>
            <relation active="#struct-1327915" type="indirect"/>
            <relation name="UMR5516" active="#struct-441569" type="direct"/>
          </listRelation>
        </org>
        <org type="institution" xml:id="struct-300036" status="VALID">
          <idno type="IdRef">110047702</idno>
          <orgName>Institut d'Optique Graduate School</orgName>
          <orgName type="acronym">IOGS</orgName>
          <desc>
            <address>
              <addrLine>2 avenue Augustin Fresnel, 91127 Palaiseau Cedex</addrLine>
              <country key="FR"/>
            </address>
            <ref type="url">https://www.institutoptique.fr</ref>
          </desc>
        </org>
        <org type="institution" xml:id="struct-300284" status="VALID">
          <idno type="IdRef">028209966</idno>
          <idno type="ISNI">0000 0001 2158 1682</idno>
          <idno type="ROR">https://ror.org/04yznqr36</idno>
          <idno type="Wikidata">Q623154</idno>
          <orgName>Université Jean Monnet - Saint-Étienne</orgName>
          <orgName type="acronym">UJM</orgName>
          <date type="start">1969-03-27</date>
          <date type="end">2025-01-01</date>
          <desc>
            <address>
              <addrLine>10, Rue Tréfilerie – CS 8230142023 Saint-Étienne Cedex 2</addrLine>
              <country key="FR"/>
            </address>
            <ref type="url">https://www.univ-st-etienne.fr/</ref>
          </desc>
          <listRelation>
            <relation active="#struct-1327915" type="direct"/>
          </listRelation>
        </org>
        <org type="regroupinstitution" xml:id="struct-1327915" status="VALID">
          <idno type="IdRef">285395831</idno>
          <orgName>Université Jean Monnet (EPSCPE)</orgName>
          <orgName type="acronym">UJM EPE</orgName>
          <date type="start">2025-01-01</date>
          <desc>
            <address>
              <addrLine>10 rue Tréfilerie42100 Saint-Etienne</addrLine>
              <country key="FR"/>
            </address>
            <ref type="url">https://www.univ-st-etienne.fr/fr/index.html</ref>
          </desc>
        </org>
        <org type="regroupinstitution" xml:id="struct-441569" status="VALID">
          <idno type="IdRef">02636817X</idno>
          <idno type="ISNI">0000000122597504</idno>
          <idno type="ROR">https://ror.org/02feahw73</idno>
          <orgName>Centre National de la Recherche Scientifique</orgName>
          <orgName type="acronym">CNRS</orgName>
          <date type="start">1939-10-19</date>
          <desc>
            <address>
              <country key="FR"/>
            </address>
            <ref type="url">https://www.cnrs.fr/</ref>
          </desc>
        </org>
      </listOrg>
      <listOrg type="projects">
        <org type="anrProject" xml:id="projanr-49679" status="VALID">
          <idno type="anr">ANR-16-IDEX-0005</idno>
          <orgName>IDEXLYON</orgName>
          <desc>IDEXLYON</desc>
          <date type="start">2016</date>
        </org>
      </listOrg>
    </back>
  </text>
</TEI>