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Divergence contractive persistante - Historique des versions
2026-04-06T05:03:06Z
Historique des versions pour cette page sur le wiki
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Pitpitt : Remplacement de texte : « ↵↵↵==Sources== » par «
==Sources== »
2024-01-29T16:13:19Z
<p>Remplacement de texte : « ↵↵↵==Sources== » par « ==Sources== »</p>
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<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Version du 29 janvier 2024 à 12:13</td>
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<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>'''Persistant contractive divergence'''</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>'''Persistant contractive divergence'''</div></td></tr>
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Pitpitt
https://datafranca.org/wiki/index.php?title=Divergence_contractive_persistante&diff=88809&oldid=prev
Pitpitt : Remplacement de texte : « ↵<small> » par «
==Sources== »
2024-01-28T02:09:38Z
<p>Remplacement de texte : « ↵<small> » par « ==Sources== »</p>
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<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Version du 27 janvier 2024 à 22:09</td>
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Pitpitt
https://datafranca.org/wiki/index.php?title=Divergence_contractive_persistante&diff=81286&oldid=prev
Pitpitt le 29 novembre 2023 à 01:08
2023-11-29T01:08:28Z
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<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Version du 28 novembre 2023 à 21:08</td>
</tr><tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l15">Ligne 15 :</td>
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<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>[https://datascience.stackexchange.com/questions/30186/understanding-contrastive-divergence Source : DataScience ]</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>[https://datascience.stackexchange.com/questions/30186/understanding-contrastive-divergence Source : DataScience ]</div></td></tr>
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<tr><td class="diff-marker" data-marker="−"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del style="font-weight: bold; text-decoration: none;">[[Catégorie:Vocabulaire]] </del></div></td><td colspan="2" class="diff-side-added"></td></tr>
<tr><td class="diff-marker" data-marker="−"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del style="font-weight: bold; text-decoration: none;">[[Catégorie:App-profond-livre]]</del></div></td><td colspan="2" class="diff-side-added"></td></tr>
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Pitpitt
https://datafranca.org/wiki/index.php?title=Divergence_contractive_persistante&diff=81273&oldid=prev
Mariealfaro le 28 novembre 2023 à 17:20
2023-11-28T17:20:13Z
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<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Version du 28 novembre 2023 à 13:20</td>
</tr><tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l1">Ligne 1 :</td>
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<tr><td class="diff-marker" data-marker="−"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del style="font-weight: bold; text-decoration: none;">[[Catégorie:Vocabulaire]] </del></div></td><td colspan="2" class="diff-side-added"></td></tr>
<tr><td class="diff-marker" data-marker="−"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del style="font-weight: bold; text-decoration: none;">[[Catégorie:App-profond-livre]]</del></div></td><td colspan="2" class="diff-side-added"></td></tr>
<tr><td class="diff-marker" data-marker="−"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del style="font-weight: bold; text-decoration: none;">[[Catégorie:Apprentissage profond]] </del></div></td><td colspan="2" class="diff-side-added"></td></tr>
<tr><td class="diff-marker" data-marker="−"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del style="font-weight: bold; text-decoration: none;"></del></div></td><td colspan="2" class="diff-side-added"></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>== Définition ==</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>== Définition ==</div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>La divergence contractive persistante est une méthode d’apprentissage pour les machines de Boltzmann restreintes, qui sont des modèles probabilistes non supervisés utilisés pour l’apprentissage profond. La divergence contractive persistante est une variante de la divergence contractive, qui est une approximation de la vraisemblance du modèle. Elle utilise un échantillonnage de Gibbs plus long pour réduire le biais de l’approximation.</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>La divergence contractive persistante est une méthode d’apprentissage pour les machines de Boltzmann restreintes, qui sont des modèles probabilistes non supervisés utilisés pour l’apprentissage profond. La divergence contractive persistante est une variante de la divergence contractive, qui est une approximation de la vraisemblance du modèle. Elle utilise un échantillonnage de Gibbs plus long pour réduire le biais de l’approximation.</div></td></tr>
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<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>[https://www.apprentissageprofond.org/ Source : ''L'apprentissage profond'', Ian Goodfellow, Yoshua Bengio et Aaron Courville Éd. Massot 2018 ]</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>[https://www.apprentissageprofond.org/ Source : ''L'apprentissage profond'', Ian Goodfellow, Yoshua Bengio et Aaron Courville Éd. Massot 2018 ]</div></td></tr>
<tr><td class="diff-marker" data-marker="−"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>[https://datascience.stackexchange.com/questions/30186/understanding-contrastive-divergence Source : DataScience]</div></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>[https://datascience.stackexchange.com/questions/30186/understanding-contrastive-divergence Source : DataScience <ins style="font-weight: bold; text-decoration: none;">]</ins></div></td></tr>
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Mariealfaro
https://datafranca.org/wiki/index.php?title=Divergence_contractive_persistante&diff=81272&oldid=prev
Mariealfaro le 28 novembre 2023 à 17:19
2023-11-28T17:19:25Z
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<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Version du 28 novembre 2023 à 13:19</td>
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<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">[[Catégorie:Vocabulaire]] </ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">[[Catégorie:App-profond-livre]]</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">[[Catégorie:Apprentissage profond]] </ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"></ins></div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>== Définition ==</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>== Définition ==</div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>La divergence contractive persistante est une méthode d’apprentissage pour les machines de Boltzmann restreintes, qui sont des modèles probabilistes non supervisés utilisés pour l’apprentissage profond. La divergence contractive persistante est une variante de la divergence contractive, qui est une approximation de la vraisemblance du modèle. Elle utilise un échantillonnage de Gibbs plus long pour réduire le biais de l’approximation.</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>La divergence contractive persistante est une méthode d’apprentissage pour les machines de Boltzmann restreintes, qui sont des modèles probabilistes non supervisés utilisés pour l’apprentissage profond. La divergence contractive persistante est une variante de la divergence contractive, qui est une approximation de la vraisemblance du modèle. Elle utilise un échantillonnage de Gibbs plus long pour réduire le biais de l’approximation.</div></td></tr>
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<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br/></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br/></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br/></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br/></td></tr>
<tr><td class="diff-marker" data-marker="−"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>[https://www.apprentissageprofond.org/ Source : ''L'apprentissage profond'', Ian Goodfellow, Yoshua Bengio et Aaron Courville Éd. Massot 2018]</div></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>[https://www.apprentissageprofond.org/ Source : ''L'apprentissage profond'', Ian Goodfellow, Yoshua Bengio et Aaron Courville Éd. Massot 2018 ]</div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>[https://datascience.stackexchange.com/questions/30186/understanding-contrastive-divergence Source : DataScience]</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>[https://datascience.stackexchange.com/questions/30186/understanding-contrastive-divergence Source : DataScience]</div></td></tr>
<tr><td class="diff-marker" data-marker="−"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del style="font-weight: bold; text-decoration: none;"></del></div></td><td colspan="2" class="diff-side-added"></td></tr>
<tr><td class="diff-marker" data-marker="−"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del style="font-weight: bold; text-decoration: none;"></del></div></td><td colspan="2" class="diff-side-added"></td></tr>
<tr><td class="diff-marker" data-marker="−"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del style="font-weight: bold; text-decoration: none;">[[Catégorie:Vocabulaire]] </del></div></td><td colspan="2" class="diff-side-added"></td></tr>
<tr><td class="diff-marker" data-marker="−"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del style="font-weight: bold; text-decoration: none;">[[Catégorie:App-profond-livre]]</del></div></td><td colspan="2" class="diff-side-added"></td></tr>
<tr><td class="diff-marker" data-marker="−"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del style="font-weight: bold; text-decoration: none;">[[Catégorie:Apprentissage profond]]</del></div></td><td colspan="2" class="diff-side-added"></td></tr>
</table>
Mariealfaro
https://datafranca.org/wiki/index.php?title=Divergence_contractive_persistante&diff=81271&oldid=prev
Mariealfaro le 28 novembre 2023 à 17:18
2023-11-28T17:18:15Z
<p></p>
<table style="background-color: #fff; color: #202122;" data-mw="interface">
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<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">← Version précédente</td>
<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Version du 28 novembre 2023 à 13:18</td>
</tr><tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l1">Ligne 1 :</td>
<td colspan="2" class="diff-lineno">Ligne 1 :</td></tr>
<tr><td class="diff-marker" data-marker="−"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del style="font-weight: bold; text-decoration: none;">== en construction ==</del></div></td><td colspan="2" class="diff-side-added"></td></tr>
<tr><td class="diff-marker" data-marker="−"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del style="font-weight: bold; text-decoration: none;">[[Catégorie:Vocabulaire]] </del></div></td><td colspan="2" class="diff-side-added"></td></tr>
<tr><td class="diff-marker" data-marker="−"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del style="font-weight: bold; text-decoration: none;">[[Catégorie:App-profond-livre]]</del></div></td><td colspan="2" class="diff-side-added"></td></tr>
<tr><td class="diff-marker" data-marker="−"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del style="font-weight: bold; text-decoration: none;">[[Catégorie:Apprentissage profond]] </del></div></td><td colspan="2" class="diff-side-added"></td></tr>
<tr><td class="diff-marker" data-marker="−"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del style="font-weight: bold; text-decoration: none;"></del></div></td><td colspan="2" class="diff-side-added"></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>== Définition ==</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>== Définition ==</div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">La divergence contractive persistante est une méthode d’apprentissage pour les machines de Boltzmann restreintes, qui sont des modèles probabilistes non supervisés utilisés pour l’apprentissage profond. La divergence contractive persistante est une variante de la divergence contractive, qui est une approximation de la vraisemblance du modèle. Elle utilise un échantillonnage de Gibbs plus long pour réduire le biais de l’approximation.</ins></div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br/></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br/></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>== Français ==</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>== Français ==</div></td></tr>
<tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l15">Ligne 15 :</td>
<td colspan="2" class="diff-lineno">Ligne 11 :</td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div><small></div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div><small></div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br/></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br/></td></tr>
<tr><td class="diff-marker" data-marker="−"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del style="font-weight: bold; text-decoration: none;">[https://www.leslibraires.ca/livres/l-apprentissage-profond-ian-goodfellow-9791097160432.html <small></del></div></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div> </div></td></tr>
<tr><td class="diff-marker" data-marker="−"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>[https://www.apprentissageprofond.org/ Source : ''L'apprentissage profond'', Ian Goodfellow, Yoshua Bengio et Aaron Courville Éd. Massot 2018 ]</div></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>[https://www.apprentissageprofond.org/ Source : ''L'apprentissage profond'', Ian Goodfellow, Yoshua Bengio et Aaron Courville Éd. Massot 2018<ins style="font-weight: bold; text-decoration: none;">]</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">[https://datascience.stackexchange.com/questions/30186/understanding-contrastive-divergence Source : DataScience]</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div> </div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div> </div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">[[Catégorie:Vocabulaire]] </ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">[[Catégorie:App-profond-livre]]</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">[[Catégorie:Apprentissage profond]</ins>]</div></td></tr>
</table>
Mariealfaro
https://datafranca.org/wiki/index.php?title=Divergence_contractive_persistante&diff=32342&oldid=prev
Pitpitt le 9 juin 2020 à 02:06
2020-06-09T02:06:28Z
<p></p>
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<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Version du 8 juin 2020 à 22:06</td>
</tr><tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l5">Ligne 5 :</td>
<td colspan="2" class="diff-lineno">Ligne 5 :</td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br/></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br/></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>== Définition ==</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>== Définition ==</div></td></tr>
<tr><td class="diff-marker" data-marker="−"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del style="font-weight: bold; text-decoration: none;">...</del></div></td><td colspan="2" class="diff-side-added"></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br/></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br/></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>== Français ==</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>== Français ==</div></td></tr>
</table>
Pitpitt
https://datafranca.org/wiki/index.php?title=Divergence_contractive_persistante&diff=22998&oldid=prev
Jacques : Remplacement de texte — « Source: L'apprentissage profond. Éd.Massot 2018 » par « Source : ''L'apprentissage profond'', Ian Goodfellow, Yoshua Bengio et Aaron Courville Éd. Massot 2018 »
2019-12-30T01:37:59Z
<p>Remplacement de texte — « Source: L'apprentissage profond. Éd.Massot 2018 » par « Source : ''L'apprentissage profond'', Ian Goodfellow, Yoshua Bengio et Aaron Courville Éd. Massot 2018 »</p>
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<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Version du 29 décembre 2019 à 21:37</td>
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<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>[https://www.leslibraires.ca/livres/l-apprentissage-profond-ian-goodfellow-9791097160432.html <small></div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>[https://www.leslibraires.ca/livres/l-apprentissage-profond-ian-goodfellow-9791097160432.html <small></div></td></tr>
<tr><td class="diff-marker" data-marker="−"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>[https://www.apprentissageprofond.org/ Source: L'apprentissage profond<del style="font-weight: bold; text-decoration: none;">. </del>Éd.Massot 2018 ]</div></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>[https://www.apprentissageprofond.org/ Source : <ins style="font-weight: bold; text-decoration: none;"> ''</ins>L'apprentissage profond<ins style="font-weight: bold; text-decoration: none;">'', Ian Goodfellow, Yoshua Bengio et Aaron Courville </ins>Éd. Massot 2018 ]</div></td></tr>
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Jacques
https://datafranca.org/wiki/index.php?title=Divergence_contractive_persistante&diff=22909&oldid=prev
Pitpitt le 28 décembre 2019 à 15:35
2019-12-28T15:35:41Z
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<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Version du 28 décembre 2019 à 11:35</td>
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<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br/></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br/></td></tr>
<tr><td class="diff-marker" data-marker="−"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>[https://www.leslibraires.ca/livres/l-apprentissage-profond-ian-goodfellow-9791097160432.html Source:L'apprentissage profond <del style="font-weight: bold; text-decoration: none;">acronymes</del>]</div></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>[https://www.leslibraires.ca/livres/l-apprentissage-profond-ian-goodfellow-9791097160432.html <ins style="font-weight: bold; text-decoration: none;"><small></ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">[https://www.apprentissageprofond.org/ </ins>Source: L'apprentissage profond<ins style="font-weight: bold; text-decoration: none;">. Éd.Massot 2018 </ins>]</div></td></tr>
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Pitpitt
https://datafranca.org/wiki/index.php?title=Divergence_contractive_persistante&diff=22664&oldid=prev
Pitpitt : Page créée avec « == en construction == Catégorie:Vocabulaire Catégorie:App-profond-livre Catégorie:Apprentissage profond == Définition == ... == Français == '''Diverge... »
2019-12-22T16:07:33Z
<p>Page créée avec « == en construction == <a href="/wiki/Cat%C3%A9gorie:Vocabulaire" title="Catégorie:Vocabulaire">Catégorie:Vocabulaire</a> <a href="/wiki/Cat%C3%A9gorie:App-profond-livre" title="Catégorie:App-profond-livre">Catégorie:App-profond-livre</a> <a href="/wiki/Cat%C3%A9gorie:Apprentissage_profond" title="Catégorie:Apprentissage profond">Catégorie:Apprentissage profond</a> == Définition == ... == Français == '''Diverge... »</p>
<p><b>Nouvelle page</b></p><div>== en construction ==<br />
[[Catégorie:Vocabulaire]] <br />
[[Catégorie:App-profond-livre]]<br />
[[Catégorie:Apprentissage profond]] <br />
<br />
== Définition ==<br />
...<br />
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== Français ==<br />
'''Divergence contractive persistante'''<br />
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== Anglais ==<br />
'''Persistant contractive divergence'''<br />
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<small><br />
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[https://www.leslibraires.ca/livres/l-apprentissage-profond-ian-goodfellow-9791097160432.html Source:L'apprentissage profond acronymes]</div>
Pitpitt