Essec\Faculty\Model\Contribution {#2216
  #_index: "academ_contributions"
  #_id: "13907"
  #_source: array:26 [
    "id" => "13907"
    "slug" => "sparse-single-index-model"
    "yearMonth" => "2013-01"
    "year" => "2013"
    "title" => "Sparse Single-Index Model"
    "description" => "ALQUIER, P. et BIAU, G. (2013). Sparse Single-Index Model. <i>Journal of Machine Learning Research</i>, 14, pp. 243-280."
    "authors" => array:2 [
      0 => array:3 [
        "name" => "ALQUIER Pierre"
        "bid" => "B00809923"
        "slug" => "alquier-pierre"
      ]
      1 => array:1 [
        "name" => "BIAU Gérard"
      ]
    ]
    "ouvrage" => ""
    "keywords" => array:6 [
      0 => "single-index model"
      1 => "sparsity"
      2 => "regression estimation"
      3 => "PAC-Bayesian"
      4 => "oracle inequality"
      5 => "reversible jump Markov chain Monte Carlo method"
    ]
    "updatedAt" => "2024-10-31 13:51:19"
    "publicationUrl" => "https://jmlr.csail.mit.edu/papers/v14/alquier13a.html"
    "publicationInfo" => array:3 [
      "pages" => "243-280"
      "volume" => "14"
      "number" => null
    ]
    "type" => array:2 [
      "fr" => "Articles"
      "en" => "Journal articles"
    ]
    "support_type" => array:2 [
      "fr" => "Revue scientifique"
      "en" => "Scientific journal"
    ]
    "countries" => array:2 [
      "fr" => "États-Unis"
      "en" => "United States of America"
    ]
    "abstract" => array:2 [
      "fr" => "We consider the single-index model estimation problem from a sparsity perspective using a PAC-Bayesian approach. On the theoretical side, we offer a sharp oracle inequality, which is more powerful than the best known oracle inequalities for other common procedures of single-index recovery. The proposed method is implemented by means of the reversible jump Markov chain Monte Carlo technique and its performance is compared with that of standard procedures."
      "en" => "We consider the single-index model estimation problem from a sparsity perspective using a PAC-Bayesian approach. On the theoretical side, we offer a sharp oracle inequality, which is more powerful than the best known oracle inequalities for other common procedures of single-index recovery. The proposed method is implemented by means of the reversible jump Markov chain Monte Carlo technique and its performance is compared with that of standard procedures."
    ]
    "authors_fields" => array:2 [
      "fr" => "Systèmes d'Information, Data Analytics et Opérations"
      "en" => "Information Systems, Data Analytics and Operations"
    ]
    "indexedAt" => "2024-11-21T09:21:53.000Z"
    "docTitle" => "Sparse Single-Index Model"
    "docSurtitle" => "Journal articles"
    "authorNames" => "<a href="/cv/alquier-pierre">ALQUIER Pierre</a>, BIAU Gérard"
    "docDescription" => "<span class="document-property-authors">ALQUIER Pierre, BIAU Gérard</span><br><span class="document-property-authors_fields">Information Systems, Data Analytics and Operations</span> | <span class="document-property-year">2013</span>"
    "keywordList" => "<a href="#">single-index model</a>, <a href="#">sparsity</a>, <a href="#">regression estimation</a>, <a href="#">PAC-Bayesian</a>, <a href="#">oracle inequality</a>, <a href="#">reversible jump Markov chain Monte Carlo method</a>"
    "docPreview" => "<b>Sparse Single-Index Model</b><br><span>2013-01 | Journal articles </span>"
    "docType" => "research"
    "publicationLink" => "<a href="https://jmlr.csail.mit.edu/papers/v14/alquier13a.html" target="_blank">Sparse Single-Index Model</a>"
  ]
  +lang: "en"
  +"_type": "_doc"
  +"_score": 8.608349
  +"parent": null
}