Essec\Faculty\Model\Profile {#6196
#_id: "B00812202"
#_source: array:39 [
"bid" => "B00812202"
"academId" => "33210"
"slug" => "daudel-kamelia"
"fullName" => "Kamélia DAUDEL"
"lastName" => "DAUDEL"
"firstName" => "Kamélia"
"title" => array:2 [
"fr" => "Professeur assistant"
"en" => "Assistant Professor"
]
"email" => "kamelia.daudel@essec.edu"
"status" => "ACTIF"
"campus" => "Campus de Cergy"
"departments" => []
"phone" => ""
"sites" => []
"facNumber" => "33210"
"externalCvUrl" => "https://faculty.essec.edu/cv/daudel-kamelia/pdf"
"googleScholarUrl" => "https://scholar.google.com/citations?hl=en&user=q1xj2FgAAAAJ"
"facOrcId" => "https://orcid.org/"
"career" => array:2 [
0 => Essec\Faculty\Model\CareerItem {#6201
#_index: null
#_id: null
#_source: array:7 [
"startDate" => "2023-09-01"
"endDate" => null
"isInternalPosition" => true
"type" => array:2 [
"fr" => "Positions académiques principales"
"en" => "Full-time academic appointments"
]
"label" => array:2 [
"fr" => "Professeur assistant"
"en" => "Assistant Professor"
]
"institution" => array:2 [
"fr" => "ESSEC Business School"
"en" => "ESSEC Business School"
]
"country" => array:2 [
"fr" => "France"
"en" => "France"
]
]
+lang: "fr"
+"parent": Essec\Faculty\Model\Profile {#6196}
}
1 => Essec\Faculty\Model\CareerItem {#6195
#_index: null
#_id: null
#_source: array:7 [
"startDate" => "2021-09-01"
"endDate" => "2022-12-31"
"isInternalPosition" => true
"type" => array:2 [
"fr" => "Positions académiques principales"
"en" => "Full-time academic appointments"
]
"label" => array:2 [
"fr" => "Post-Doctorante"
"en" => "Post-Doctorate"
]
"institution" => array:2 [
"fr" => "University of Oxford"
"en" => "University of Oxford"
]
"country" => array:2 [
"fr" => "Royaume-Uni"
"en" => "United Kingdom"
]
]
+lang: "fr"
+"parent": Essec\Faculty\Model\Profile {#6196}
}
]
"diplomes" => array:3 [
0 => Essec\Faculty\Model\Diplome {#6198
#_index: null
#_id: null
#_source: array:5 [
"diplome" => "DIPLOMA"
"year" => "2021"
"label" => array:2 [
"fr" => "Doctorat en Mathématiques Appliquées"
"en" => "Doctorat en Mathématiques Appliquées"
]
"institution" => array:2 [
"fr" => "Télécom Paris"
"en" => "Télécom Paris"
]
"country" => array:2 [
"fr" => "France"
"en" => "France"
]
]
+lang: "fr"
+"parent": Essec\Faculty\Model\Profile {#6196}
}
1 => Essec\Faculty\Model\Diplome {#6200
#_index: null
#_id: null
#_source: array:5 [
"diplome" => "DIPLOMA"
"year" => "2018"
"label" => array:2 [
"fr" => "MSc in Mathematical and Computational Finance"
"en" => "MSc in Mathematical and Computational Finance"
]
"institution" => array:2 [
"fr" => "University of Oxford"
"en" => "University of Oxford"
]
"country" => array:2 [
"fr" => "Royaume-Uni"
"en" => "United Kingdom"
]
]
+lang: "fr"
+"parent": Essec\Faculty\Model\Profile {#6196}
}
2 => Essec\Faculty\Model\Diplome {#6197
#_index: null
#_id: null
#_source: array:5 [
"diplome" => "DIPLOMA"
"year" => "2018"
"label" => array:2 [
"fr" => "Diplôme d’Ingénieur"
"en" => "Diplôme d’Ingénieur"
]
"institution" => array:2 [
"fr" => "Télécom Paris"
"en" => "Télécom Paris"
]
"country" => array:2 [
"fr" => "France"
"en" => "France"
]
]
+lang: "fr"
+"parent": Essec\Faculty\Model\Profile {#6196}
}
]
"bio" => array:2 [
"fr" => null
"en" => null
]
"department" => array:2 [
"fr" => "Systèmes d’information, sciences de la décision et statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"site" => array:2 [
"fr" => "https://kdaudel.github.io/"
"en" => "https://kdaudel.github.io/"
]
"industrrySectors" => array:2 [
"fr" => null
"en" => null
]
"researchFields" => array:2 [
"fr" => null
"en" => null
]
"teachingFields" => array:2 [
"fr" => null
"en" => null
]
"distinctions" => array:1 [
0 => Essec\Faculty\Model\Distinction {#6199
#_index: null
#_id: null
#_source: array:6 [
"date" => "2022-07-01"
"label" => array:2 [
"fr" => "Premier Prix de Thèse 2022 de l'Institut Polytechnique de Paris"
"en" => "First prize of Institut Polytechnique de Paris Best Thesis Award 2022"
]
"type" => array:2 [
"fr" => "Prix"
"en" => "Awards"
]
"tri" => " 1 "
"institution" => array:2 [
"fr" => null
"en" => null
]
"country" => array:2 [
"fr" => null
"en" => null
]
]
+lang: "fr"
+"parent": Essec\Faculty\Model\Profile {#6196}
}
]
"teaching" => []
"otherActivities" => []
"theses" => []
"indexedAt" => "2023-12-11T17:21:22.000Z"
"contributions" => array:5 [
0 => Essec\Faculty\Model\Contribution {#6202
#_index: "academ_contributions"
#_id: "14316"
#_source: array:18 [
"id" => "14316"
"slug" => "infinite-dimensional-gradient-based-descent-for-alpha-divergence-minimisation"
"yearMonth" => "2021-08"
"year" => "2021"
"title" => "Infinite-dimensional gradient-based descent for alpha-divergence minimisation"
"description" => "DAUDEL, K., DOUC, R. et PORTIER, F. (2021). Infinite-dimensional gradient-based descent for alpha-divergence minimisation. <i>Annals of Statistics</i>, 49(4), pp. 2250 - 2270."
"authors" => array:3 [
0 => array:3 [
"name" => "DAUDEL Kamélia"
"bid" => "B00812202"
"slug" => "daudel-kamelia"
]
1 => array:1 [
"name" => "DOUC Randal"
]
2 => array:1 [
"name" => "PORTIER François"
]
]
"ouvrage" => ""
"keywords" => []
"updatedAt" => "2023-09-12 15:34:27"
"publicationUrl" => "https://projecteuclid.org/journals/annals-of-statistics/volume-49/issue-4/Infinite-dimensional-gradient-based-descent-for-alpha-divergence-minimisation/10.1214/20-AOS2035.short"
"publicationInfo" => array:3 [
"pages" => "2250 - 2270"
"volume" => "49"
"number" => "4"
]
"type" => array:2 [
"fr" => "Articles"
"en" => "Journal articles"
]
"support_type" => array:2 [
"fr" => "Revue scientifique"
"en" => "Scientific journal"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "We demonstrate empirically on both toy and real-world examples the benefit of using the Power Descent and going beyond the Entropic Mirror Descent framework, which fails as the dimension grows."
"en" => "We demonstrate empirically on both toy and real-world examples the benefit of using the Power Descent and going beyond the Entropic Mirror Descent framework, which fails as the dimension grows."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"indexedAt" => "2023-12-11T17:22:11.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 7.379551
+"parent": null
}
1 => Essec\Faculty\Model\Contribution {#6204
#_index: "academ_contributions"
#_id: "14317"
#_source: array:18 [
"id" => "14317"
"slug" => "monotonic-alpha-divergence-minimisation-for-variational-inference"
"yearMonth" => "2023-01"
"year" => "2023"
"title" => "Monotonic Alpha-divergence Minimisation for Variational Inference"
"description" => "DAUDEL, K., DOUC, R. et ROUEFF, F. (2023). Monotonic Alpha-divergence Minimisation for Variational Inference. <i>Journal of Machine Learning Research</i>, 24(62), pp. 1-76."
"authors" => array:3 [
0 => array:3 [
"name" => "DAUDEL Kamélia"
"bid" => "B00812202"
"slug" => "daudel-kamelia"
]
1 => array:1 [
"name" => "DOUC Randal"
]
2 => array:1 [
"name" => "ROUEFF François"
]
]
"ouvrage" => ""
"keywords" => []
"updatedAt" => "2023-09-12 15:45:42"
"publicationUrl" => "http://jmlr.org/papers/v24/21-0249.html"
"publicationInfo" => array:3 [
"pages" => "1-76"
"volume" => "24"
"number" => "62"
]
"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" => """
In this paper, we introduce a novel family of iterative algorithms which carry out α\n
-divergence minimisation in a Variational Inference context. They do so by ensuring a systematic decrease at each step in the α\n
-divergence between the variational and the posterior distributions. In its most general form, the variational distribution is a mixture model and our framework allows us to simultaneously optimise the weights and components parameters of this mixture model. Our approach permits us to build on various methods previously proposed for α\n
-divergence minimisation such as Gradient or Power Descent schemes and we also shed a new light on an integrated Expectation Maximization algorithm. Lastly, we provide empirical evidence that our methodology yields improved results on several multimodal target distributions and on a real data example.
"""
"en" => """
In this paper, we introduce a novel family of iterative algorithms which carry out α\n
-divergence minimisation in a Variational Inference context. They do so by ensuring a systematic decrease at each step in the α\n
-divergence between the variational and the posterior distributions. In its most general form, the variational distribution is a mixture model and our framework allows us to simultaneously optimise the weights and components parameters of this mixture model. Our approach permits us to build on various methods previously proposed for α\n
-divergence minimisation such as Gradient or Power Descent schemes and we also shed a new light on an integrated Expectation Maximization algorithm. Lastly, we provide empirical evidence that our methodology yields improved results on several multimodal target distributions and on a real data example.
"""
]
"authors_fields" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"indexedAt" => "2023-12-11T17:22:11.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 7.379551
+"parent": null
}
2 => Essec\Faculty\Model\Contribution {#6206
#_index: "academ_contributions"
#_id: "14318"
#_source: array:18 [
"id" => "14318"
"slug" => "alpha-divergence-variational-inference-meets-importance-weighted-auto-encoders-methodology-and-asymptotics"
"yearMonth" => "2023-08"
"year" => "2023"
"title" => "Alpha-divergence Variational Inference Meets Importance Weighted Auto-Encoders: Methodology and Asymptotics"
"description" => "DAUDEL, K., BENTON, J., SHI, Y. et DOUCET, A. (2023). Alpha-divergence Variational Inference Meets Importance Weighted Auto-Encoders: Methodology and Asymptotics. <i>Journal of Machine Learning Research</i>, 24(243), pp. 1-83."
"authors" => array:4 [
0 => array:3 [
"name" => "DAUDEL Kamélia"
"bid" => "B00812202"
"slug" => "daudel-kamelia"
]
1 => array:1 [
"name" => "BENTON Joe"
]
2 => array:1 [
"name" => "SHI Yuyang"
]
3 => array:1 [
"name" => "DOUCET Arnaud"
]
]
"ouvrage" => ""
"keywords" => []
"updatedAt" => "2023-09-12 15:58:22"
"publicationUrl" => "https://www.jmlr.org/papers/volume24/22-1160/22-1160.pdf"
"publicationInfo" => array:3 [
"pages" => "1-83"
"volume" => "24"
"number" => "243"
]
"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" => ""
"en" => ""
]
"authors_fields" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"indexedAt" => "2023-12-11T17:22:11.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 7.379551
+"parent": null
}
3 => Essec\Faculty\Model\Contribution {#6203
#_index: "academ_contributions"
#_id: "14319"
#_source: array:18 [
"id" => "14319"
"slug" => "mixture-weights-optimisation-for-alpha-divergence-variational-inference"
"yearMonth" => "2021-12"
"year" => "2021"
"title" => "Mixture weights optimisation for Alpha-Divergence Variational Inference"
"description" => "DAUDEL, K. et DOUC, R. (2021). Mixture weights optimisation for Alpha-Divergence Variational Inference. Dans: <i>35th Conference on Neural Information Processing Systems (NeurIPS 2021)</i>. Curran Associates, Inc. pp. 4397–4408."
"authors" => array:2 [
0 => array:3 [
"name" => "DAUDEL Kamélia"
"bid" => "B00812202"
"slug" => "daudel-kamelia"
]
1 => array:1 [
"name" => "DOUC Randal"
]
]
"ouvrage" => "35th Conference on Neural Information Processing Systems (NeurIPS 2021)"
"keywords" => []
"updatedAt" => "2023-09-12 01:00:39"
"publicationUrl" => "https://proceedings.neurips.cc/paper_files/paper/2021/file/233f1dd0f3f537bcb7a338ea74d63483-Paper.pdf"
"publicationInfo" => array:3 [
"pages" => "4397–4408"
"volume" => ""
"number" => ""
]
"type" => array:2 [
"fr" => "Actes d'une conférence"
"en" => "Conference Proceedings"
]
"support_type" => array:2 [
"fr" => "Editeur"
"en" => "Publisher"
]
"countries" => array:2 [
"fr" => "États-Unis"
"en" => "United States of America"
]
"abstract" => array:2 [
"fr" => ""
"en" => ""
]
"authors_fields" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"indexedAt" => "2023-12-11T17:22:11.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 7.379551
+"parent": null
}
4 => Essec\Faculty\Model\Contribution {#6207
#_index: "academ_contributions"
#_id: "14350"
#_source: array:18 [
"id" => "14350"
"slug" => "alpha-divergence-variational-inference-meets-importance-weighted-auto-encoders-methodology-and-asymptotics"
"yearMonth" => "2023-12"
"year" => "2023"
"title" => "Alpha-divergence Variational Inference Meets Importance Weighted Auto-Encoders: Methodology and Asymptotics"
"description" => "DAUDEL, K., BENTON, J., SHI, Y. et DOUCET, A. (2023). Alpha-divergence Variational Inference Meets Importance Weighted Auto-Encoders: Methodology and Asymptotics. Dans: 37th Conference on Neural Information Processing Systems 2023 (NeurIPS 2023). New-Orleans."
"authors" => array:4 [
0 => array:3 [
"name" => "DAUDEL Kamélia"
"bid" => "B00812202"
"slug" => "daudel-kamelia"
]
1 => array:1 [
"name" => "BENTON Joe"
]
2 => array:1 [
"name" => "SHI Yuyang"
]
3 => array:1 [
"name" => "DOUCET Arnaud"
]
]
"ouvrage" => "37th Conference on Neural Information Processing Systems 2023 (NeurIPS 2023)"
"keywords" => []
"updatedAt" => "2023-09-27 01:00:43"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => ""
"volume" => ""
"number" => ""
]
"type" => array:2 [
"fr" => "Communications dans une conférence"
"en" => "Presentations at an Academic or Professional conference"
]
"support_type" => array:2 [
"fr" => null
"en" => null
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => ""
"en" => ""
]
"authors_fields" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"indexedAt" => "2023-12-11T17:22:11.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 7.379551
+"parent": null
}
]
"avatar" => "https://faculty.essec.edu/wp-content/uploads/avatars/B00812202.jpg"
"contributionCounts" => 5
"personalLinks" => array:2 [
0 => "<a href="https://orcid.org/" target="_blank">ORCID</a>"
1 => "<a href="https://scholar.google.com/citations?hl=en&user=q1xj2FgAAAAJ" target="_blank">Google scholar</a>"
]
"docTitle" => "Kamélia DAUDEL"
"docSubtitle" => "Professeur assistant"
"docDescription" => "Département: Systèmes d’information, sciences de la décision et statistiques<br>Campus de Cergy"
"docType" => "cv"
"docPreview" => "<img src="https://faculty.essec.edu/wp-content/uploads/avatars/B00812202.jpg"><span><span>Kamélia DAUDEL</span><span>B00812202</span></span>"
]
#_index: "academ_cv"
+lang: "fr"
+"_type": "_doc"
+"_score": 4.862393
+"parent": null
}
