Essec\Faculty\Model\Contribution {#2216
  #_index: "academ_contributions"
  #_id: "14619"
  #_source: array:26 [
    "id" => "14619"
    "slug" => "robust-estimation-and-regression-with-mmd"
    "yearMonth" => "2024-01"
    "year" => "2024"
    "title" => "Robust estimation and regression with MMD"
    "description" => "ALQUIER, P. et GERBER, M. (2024). Robust estimation and regression with MMD. Dans: The Mathematics of Data: Workshop on Optimization and Discrete Structures. Singapore."
    "authors" => array:2 [
      0 => array:3 [
        "name" => "ALQUIER Pierre"
        "bid" => "B00809923"
        "slug" => "alquier-pierre"
      ]
      1 => array:1 [
        "name" => "GERBER Mathieu"
      ]
    ]
    "ouvrage" => "The Mathematics of Data: Workshop on Optimization and Discrete Structures"
    "keywords" => array:2 [
      0 => "Maximum Mean Discrepancy"
      1 => "robustness"
    ]
    "updatedAt" => "2024-01-04 11:15:43"
    "publicationUrl" => null
    "publicationInfo" => array:3 [
      "pages" => ""
      "volume" => ""
      "number" => ""
    ]
    "type" => array:2 [
      "fr" => "Invité dans une conférence académique (Keynote speaker)"
      "en" => "Invited speaker at an academic conference"
    ]
    "support_type" => array:2 [
      "fr" => null
      "en" => null
    ]
    "countries" => array:2 [
      "fr" => null
      "en" => null
    ]
    "abstract" => array:2 [
      "fr" => "Maximum Mean Discrepancy (MMD, based on suitable kernels) leads to estimation procedures that are consistent without any assumption on the model nor on the data-generating process. This leads to strong robustness properties in practice, and this method was already used in complex models with promising results: estimation of SDE coefficients, ccopulas, data compression, generative models in AI."
      "en" => "Maximum Mean Discrepancy (MMD, based on suitable kernels) leads to estimation procedures that are consistent without any assumption on the model nor on the data-generating process. This leads to strong robustness properties in practice, and this method was already used in complex models with promising results: estimation of SDE coefficients, ccopulas, data compression, generative models in AI."
    ]
    "authors_fields" => array:2 [
      "fr" => "Systèmes d'Information, Data Analytics et Opérations"
      "en" => "Information Systems, Data Analytics and Operations"
    ]
    "indexedAt" => "2024-12-22T01:21:46.000Z"
    "docTitle" => "Robust estimation and regression with MMD"
    "docSurtitle" => "Invited speaker at an academic conference"
    "authorNames" => "<a href="/cv/alquier-pierre">ALQUIER Pierre</a>, GERBER Mathieu"
    "docDescription" => "<span class="document-property-authors">ALQUIER Pierre, GERBER Mathieu</span><br><span class="document-property-authors_fields">Information Systems, Data Analytics and Operations</span> | <span class="document-property-year">2024</span>"
    "keywordList" => "<a href="#">Maximum Mean Discrepancy</a>, <a href="#">robustness</a>"
    "docPreview" => "<b>Robust estimation and regression with MMD</b><br><span>2024-01 | Invited speaker at an academic conference </span>"
    "docType" => "research"
    "publicationLink" => "<a href="#" target="_blank">Robust estimation and regression with MMD</a>"
  ]
  +lang: "en"
  +"_type": "_doc"
  +"_score": 8.135556
  +"parent": null
}