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Using Dependency Syntax-Based Methods for Automatic Detection of Psychiatric Comorbidities
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In: Resources and ProcessIng of linguistic, para-linguistic and extra-linguistic Data from people with various forms of cognitive/psychiatric/developmental impairments ; https://hal-imt-atlantique.archives-ouvertes.fr/hal-02861753 ; Resources and ProcessIng of linguistic, para-linguistic and extra-linguistic Data from people with various forms of cognitive/psychiatric/developmental impairments, May 2020, Marseille, France. pp.142-150 ; https://spraakbanken.gu.se/en/rapid-2020 (2020)
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| 22 |
Modélisation et interprétation des catégories taxonomiques des animaux et aliments chez des enfants d'âge préscolaire
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In: Extraction et Gestion des connaissances (EGC) ; https://hal.archives-ouvertes.fr/hal-02469861 ; Extraction et Gestion des connaissances (EGC), Jan 2020, Bruxelles, Belgique. pp.245-252 ; https://www.egc.asso.fr/category/publications/actes-egc (2020)
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| 23 |
Standard-based Lexical Models for Automatically Structured Dictionaries ; Modèles lexicaux standardisés pour les dictionnaires à structure automatique
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In: https://tel.archives-ouvertes.fr/tel-03153438 ; Computation and Language [cs.CL]. Université de Paris, 2020. English (2020)
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Question Answering with Hybrid Data and Models ; Question-réponse utilisant des données et modèles hybrides
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In: https://tel.archives-ouvertes.fr/tel-02890467 ; Document and Text Processing. Université Paris-Saclay, 2020. English. ⟨NNT : 2020UPASS024⟩ (2020)
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| 25 |
Privacy Amplification by Decentralization
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In: https://hal.inria.fr/hal-03100005 ; 2020 (2020)
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Abstract:
Analyzing data owned by several parties while achieving a good trade-off between utility and privacy is a key challenge in federated learning and analytics. In this work, we introduce a novel relaxation of local differential privacy (LDP) that naturally arises in fully decentralized algorithms, i.e., when participants exchange information by communicating along the edges of a network graph without central coordinator. This relaxation, that we call network DP, captures the fact that users have only a local view of the system. To show the relevance of network DP, we study a decentralized model of computation where a token performs a walk on the network graph and is updated sequentially by the party who receives it. For tasks such as real summation, histogram computation and optimization with gradient descent, we propose simple algorithms on ring and complete topologies. We prove that the privacy-utility trade-offs of our algorithms under network DP significantly improve upon what is achievable under LDP (sometimes even matching the utility of the trusted curator model), showing for the first time that formal privacy gains can be obtained from full decentralization. Our experiments illustrate the improved utility of our approach for decentralized training with stochastic gradient descent.
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Keyword:
[INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG]; [STAT.ML]Statistics [stat]/Machine Learning [stat.ML]
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URL: https://hal.inria.fr/hal-03100005v3/file/2012.05326.pdf
https://hal.inria.fr/hal-03100005v3/document
https://hal.inria.fr/hal-03100005
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| 26 |
Distributed Differentially Private Averaging with Improved Utility and Robustness to Malicious Parties
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In: NeurIPS 2020 workshop on Privacy Preserving Machine Learning - PriML and PPML Joint Edition ; https://hal.archives-ouvertes.fr/hal-03117816 ; NeurIPS 2020 workshop on Privacy Preserving Machine Learning - PriML and PPML Joint Edition, Dec 2020, Vancouver (Virtual Workshop), Canada ; https://ppml-workshop.github.io/ (2020)
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| 27 |
Privacy Amplification by Decentralization
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In: https://hal.inria.fr/hal-03100005 ; 2020 (2020)
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| 28 |
Fully Decentralized Joint Learning of Personalized Models and Collaboration Graphs
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In: AISTATS 2020 - The 23rd International Conference on Artificial Intelligence and Statistics ; https://hal.inria.fr/hal-03100057 ; AISTATS 2020 - The 23rd International Conference on Artificial Intelligence and Statistics, Aug 2020, Palerme / Virtual, Italy ; https://aistats.org/aistats2020/ (2020)
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| 29 |
Échange de bruit corrélé pour le calcul distribué de moyenne avec garanties de confidentialité différentielle
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In: Conférence sur l'Apprentissage Automatique 2020 ; https://hal.archives-ouvertes.fr/hal-03117907 ; Conférence sur l'Apprentissage Automatique 2020, Jun 2020, Vannes (Virtual), France ; https://cap-rfiap2020.sciencesconf.org/ (2020)
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| 30 |
Distributed Differentially Private Averaging with Improved Utility and Robustness to Malicious Parties
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In: https://hal.inria.fr/hal-03100019 ; 2020 (2020)
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| 31 |
Private Protocols for U-Statistics in the Local Model and Beyond
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In: AISTATS 2020 - 23rd International Conference on Artificial Intelligence and Statistics ; https://hal.inria.fr/hal-02310236 ; AISTATS 2020 - 23rd International Conference on Artificial Intelligence and Statistics, Aug 2020, Palermo, Italy (2020)
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| 32 |
Automatic Processing of Aerodynamic Parameters in Parkinsonian Dysarthria
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In: Automatic Assessment of Parkinosnian Speech. Ed. Springer Nature Switzerland AG. Communications in Computer and Information Science (CCIS) Series, Vol 1295. ; https://hal.archives-ouvertes.fr/hal-03115366 ; Automatic Assessment of Parkinosnian Speech. Ed. Springer Nature Switzerland AG. Communications in Computer and Information Science (CCIS) Series, Vol 1295., pp.60-76, 2020, ⟨10.1007/978-3-030-65654-6_4⟩ (2020)
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| 33 |
Evaluating the Potential Gain of Auditory and Audiovisual Speech-Predictive Coding Using Deep Learning
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In: ISSN: 0899-7667 ; EISSN: 1530-888X ; Neural Computation ; https://hal.archives-ouvertes.fr/hal-03016083 ; Neural Computation, Massachusetts Institute of Technology Press (MIT Press), 2020, 32 (3), pp.596-625. ⟨10.1162/neco_a_01264⟩ (2020)
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| 34 |
NLU-Co at SemEval-2020 Task 5: NLU/SVM based model apply to characterise and extract counterfactual items on raw data
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In: COLING ; SemEval-2020 (International Workshop on Semantic Evaluation 2020) ; https://hal.archives-ouvertes.fr/hal-03119450 ; SemEval-2020 (International Workshop on Semantic Evaluation 2020), Dec 2020, Barcelone, Spain. pp.670-676 ; https://www.aclweb.org/anthology/2020.semeval-1.87 (2020)
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| 35 |
Can Knowledge Graph Embeddings Tell Us What Fact-checked Claims Are About?
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In: Proceedings of the Workshop on Insights from Negative Results in NLP ; Workshop on Insights from Negative Results in NLP ; https://hal.mines-ales.fr/hal-02986882 ; Workshop on Insights from Negative Results in NLP, Nov 2020, Online, Dominican Republic. ⟨10.18653/v1/2020.insights-1.11⟩ ; https://insights-workshop.github.io/ (2020)
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| 36 |
SMAD: A tool for automatically annotating the smile intensity along a video record
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In: HRC2020, 10th Humour Research Conference ; https://hal.archives-ouvertes.fr/hal-02529371 ; HRC2020, 10th Humour Research Conference, Mar 2020, Commerce, Texas, United States (2020)
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| 37 |
NTeALan Dictionaries Platforms: An Example Of Collaboration-Based Model
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In: Proceedings of the 1st International Workshop on Language Technology Platforms (IWLTP 2020) ; https://hal.archives-ouvertes.fr/hal-02701912 ; Proceedings of the 1st International Workshop on Language Technology Platforms (IWLTP 2020), 2020, pp.11 - 16 (2020)
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| 38 |
Building Collaboration-based Resources In Endowed African Languages: Case Of NTeALan Dictionaries Platform
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In: Proceedings of the First workshop on Resources for African Indigenous Languages (RAIL) ; https://hal.archives-ouvertes.fr/hal-02701162 ; Proceedings of the First workshop on Resources for African Indigenous Languages (RAIL), 2020 (2020)
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| 39 |
NLU-Co at SemEval-2020 Task 5: NLU/SVM based model apply to characterise and extract counterfactual items on raw data
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In: COLING ; SemEval-2020 (International Workshop on Semantic Evaluation 2020) ; https://hal.archives-ouvertes.fr/hal-03119450 ; SemEval-2020 (International Workshop on Semantic Evaluation 2020), Dec 2020, Barcelone, Spain. pp.670-676 ; https://www.aclweb.org/anthology/2020.semeval-1.87 (2020)
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| 40 |
How OCR Performance can Impact on the Automatic Extraction of Dictionary Content Structures
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In: 19th annual Conference and Members’ Meeting of the Text Encoding Initiative Consortium (TEI) -What is text, really? TEI and beyond ; https://hal.archives-ouvertes.fr/hal-02263276 ; 19th annual Conference and Members’ Meeting of the Text Encoding Initiative Consortium (TEI) -What is text, really? TEI and beyond, Sep 2019, Graz, Austria (2019)
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