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DTSTART;TZID=Europe/Paris:20210401T130000
DTEND;TZID=Europe/Paris:20210401T143000
DTSTAMP:20260519T161142
CREATED:20210319T134650Z
LAST-MODIFIED:20210330T154147Z
UID:11789-1617282000-1617287400@www.loria.fr
SUMMARY:Colloquium Loria : Mathieu d'Aquin
DESCRIPTION:Mathieu d’Aquin\, Professor of Informatics specialised in data analytics and semantic technologies at the Data Science Institute and the Insight Centre for Data Analytics of the National University of Ireland Galway\, is the next speaker for Loria’s colloquium. \nThe colloquium will take place on Teams on Thursday\, April 1st at 1pm\, with a presentation entitled “Data and knowledge as commodities”. \nAbstract: While data has become increasingly available in the last few years\, those data and the models used to analyse them are becoming less and less interpretable. In other words\, the challenge of turning such vast amounts of data into exploitable knowledge is still present. In this presentation\, I aim to describe ongoing efforts to address this challenge by combining current data mining and machine learning techniques with traditional\, symbolic methods for artificial intelligence based on explicit knowledge representations and inferences. In particular\, taking examples from projects in education\, smart cities and the digital humanities\, I show how the legacy of the semantic web\, especially web-scale knowledge graphs and ontologies\, can support intelligent methods for data understanding and the interpretability of machine learning models.
URL:https://www.loria.fr/event/colloquium-loria-mathieu-daquin/
CATEGORIES:Colloquium Loria
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Paris:20210402T140000
DTEND;TZID=Europe/Paris:20210402T163000
DTSTAMP:20260519T161142
CREATED:20210325T092335Z
LAST-MODIFIED:20210325T092633Z
UID:11837-1617372000-1617381000@www.loria.fr
SUMMARY:We are the robots - Basic Bot\, performance théâtre et robotique
DESCRIPTION:Rendez-vous le vendredi 2 avril à 14h pour “Basic Bot”\, une performance théâtre et robotique proposée dans le cadre de l’atelier Artem « We Are The Robots »\, avec une pièce de théâtre numérique suivie d’une conférence-débat en direct sur la page Facebook de Mines Nancy. \nUn événement conçu par les élèves de Mines Nancy\, d’ICN Business School et de l’ENSAD.\nDirection scientifique et technique : Patrick Hénaff\, enseignant-chercheur Mines Nancy / Loria\, et Alain Dutech\, chargé de recherche Inria au Loria.\nDirection artistique : Raphaël Gouisset\, Collectif Les Particules \n \nL’intrigue du spectacle a lieu durant le confinement lorsque les étudiants sont livrés à eux-mêmes et se retrouvent seuls dans leur chambre. Ils décident alors de se distraire en cherchant des activités sur internet et découvrent le site BASIC BOT\, une salle de sport 3.0 où les étudiants suivent des coachs robots à travers des vidéos. Les robots se révèlent être plus ou moins doués de sentiments et de compréhension pour les accompagner dans cette période très singulière.  \nLe spectacle sera suivi d’un débat avec les étudiants du projet et des professionnels de la robotique et de l’intelligence artificielle : Raja Chatila (professeur\, directeur de l’ISIR)\, Nazim Fates (chargé de recherche Inria au Loria)\, Eloïse Dalin (doctorante dans l’équipe Larsen) pour répondre aux questions du public. \nPiloté par Patrick Henaff\, ce projet est un espace de travail transdisciplinaire\, entre composition artistique et programmation robotique. Il aborde les sujets de l’anthropomorphisme (attribution de caractéristiques du comportement humains ou de la morphologie humaine à des objets)\, de l’intelligence artificielle (IA)\, des questionnements sociétaux soulevés par la robotique et enfin\,  du rôle du roboticien et de son « pouvoir d’agir » dans une société où la robotique sera de plus en plus présente. Cet atelier est donc un travail collaboratif où les qualités et désirs de chaque participant se concrétisent pour parvenir à une réalisation commune. \nLe spectacle sera diffusé en live sur la page Facebook de Mines Nancy \nCe projet est une collaboration entre Mines Nancy\, ICN Business School\, l’ENSAD et un partenariat avec l’Alliance Artem et le Loria (CNRS\, Inria\, Université de Lorraine). Les robots de Mines Nancy ont été mis à disposition pour ce projet afin d’offrir un spectacle divertissant.
URL:https://www.loria.fr/event/we-are-the-robots-basic-bot-performance-theatre-et-robotique/
CATEGORIES:Manifestation
ATTACH;FMTTYPE=image/jpeg:https://www.loria.fr/wp-content/uploads/2021/03/Affiche-finale-scaled.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Paris:20210409T110000
DTEND;TZID=Europe/Paris:20210409T120000
DTSTAMP:20260519T161142
CREATED:20210407T092250Z
LAST-MODIFIED:20210407T092250Z
UID:11971-1617966000-1617969600@www.loria.fr
SUMMARY:MALOTEC Séminaire : Evaluating Local Explanation Methods on Ground Truth
DESCRIPTION:Evaluating local explanation methods is a difficult task due to the lack of a shared and universally accepted definition of explanation. In the literature\, one of the most common ways to assess the performance of an explanation method is to measure the fidelity of the explanation with respect to the classification of a black box model adopted by an Artificial Intelligent system for making a decision. However\, this kind of evaluation only measures the degree of adherence of the local explainer in reproducing the behavior of the black box classifier with respect to the final decision. Therefore\, the explanation provided by the local explainer could be different in the content even though it leads to the same decision of the AI system. We propose an approach that allows to measure to which extent the explanations returned by local explanation methods are correct with respect to a synthetic ground truth explanation. Indeed\, the proposed methodology enables the generation of synthetic transparent classifiers for which the reason for the decision taken\, i.e.\, a synthetic ground truth explanation\, is available by design. Experimental results show how the proposed approach allows to easily evaluate local explanations on the ground truth and to characterize the quality of local explanation methods. \n\n\nSpeaker:\nRiccardo Guidotti\, Assistant Professor at the Department of Computer Science (University of Pisa) and a member of the Knowledge Discovery and Data Mining Laboratory (KDDLab).\n\nOn TEAMS. More information at:\nhttps://malotec.loria.fr
URL:https://www.loria.fr/event/malotec-seminaire-evaluating-local-explanation-methods-on-ground-truth/
LOCATION:online
CATEGORIES:Séminaire
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Paris:20210415T160000
DTEND;TZID=Europe/Paris:20210415T170000
DTSTAMP:20260519T161142
CREATED:20210401T090802Z
LAST-MODIFIED:20210401T090927Z
UID:11954-1618502400-1618506000@www.loria.fr
SUMMARY:DigiTrust Webinar : Enka Blanchard
DESCRIPTION:The second webinar of LUE IMPACT project DigiTrust will take place on Thursday\, 15th April at 4pm. \nPostdoctoral Researcher Enka Blanchard\, working in the DigiTrust consortium\, will give a presentation entitled “Securing everyday voting with low-tech systems” \nThe webinar will take place on Teams. \nAbstract: \nVoting is often seen as a solemn activity\, with voters exercising their rights every few years in secure conditions. However\, many voting activities happen in much more common situations\, from company boardrooms to homeowners associations or employee breakrooms. Those votes often happen by raising one’s hand or at best writing down a name on a piece of paper and putting it into a hat. With the pandemic\, those votes have been harder to organise\, creating a vacuum for new systems to take hold\, and potentially presenting new opportunities.\n\nThe talk will start with an introduction to low-tech verifiable voting systems. We will then go over the impact of the pandemic and how it led us to propose a solution that is currently in use at the University of Maryland\, Baltimore County\, as well as the details of this low-tech (non-cryptographic) verifiable voting system. Finally\, I will discuss the implications this has not only for the development but more importantly for the deployment of new voting systems.\n\n\nThe talk is based on research I recently pursued with colleagues from UMBC and LaBRI. The relevant papers and preprints are available below:\n\nEnka Blanchard and Ted Selker. Origami voting: a non-cryptographic approach to transparent ballot verification. In VOTING – 5th Workshop on Advances in Secure Electronic\nVoting (https://hal.archives-ouvertes.fr/hal-02550738)\nEnka Blanchard\, Ryan Robucci\, Ted Selker\, and Alan T. Sherman. Phrase-verified voting: Verifiable low-tech remote boardroom voting. under review\nEnka Blanchard\, Sébastien Bouchard\, and Ted Selker. Visual secrets: A recognition-based security primitive and its use for boardroom voting. under review
URL:https://www.loria.fr/event/digitrust-webinar-enka-blanchard/
LOCATION:online
CATEGORIES:Séminaire
ATTACH;FMTTYPE=image/png:https://www.loria.fr/wp-content/uploads/2021/04/Webinaire-Enka-Blanchard.png
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20210419
DTEND;VALUE=DATE:20210421
DTSTAMP:20260519T161142
CREATED:20201203T101217Z
LAST-MODIFIED:20201203T101217Z
UID:11302-1618790400-1618963199@www.loria.fr
SUMMARY:Workshop on Human Evaluation of NLP Systems (HumEval)
DESCRIPTION:EACL’21\, Kiev\, Ukraine\, 19-20 April 2021\nFirst Call for Papers\nThe HumEval Workshop invites the submission of long and short papers on substantial\, original\, and unpublished research on all aspects of human evaluation of NLP systems\, both intrinsic and extrinsic\, including but by no means limited to NLP systems whose output is language. More on: humeval.github.io. \nInvited Speakers\n\nMohit Bansal\, UNC Chapel Hill\, US\nMargaret Mitchell\, Google\, US\nLucia Specia\, UCL\, UK\n\nImportant Dates\n\nDec 2: First Call for Workshop Papers\nDec 18: Second Call for Workshop Papers\nJan 18: Workshop Paper Due Date\nFeb 18: Notification of Acceptance\nMar 01: Camera-ready papers due\nApr 19-20: Workshop Dates\nAll deadlines are 11.59 pm UTC-12.\n\nWorkshop Topic and Content\nHuman evaluation plays a central role in NLP\, from the large-scale crowd-sourced evaluations carried out e.g. by the WMT workshops\, to the much smaller experiments routinely encountered in conference papers. Moreover\, while NLP embraced automatic evaluation metrics from BLEU (Papineni et al\, 2001) onwards\, the field has always been acutely aware of their limitations (Callison-Burch et al.\, 2006; Reiter and Belz\, 2009; Novikova et al.\, 2017; Reiter\, 2018)\, and has gauged their trustworthiness in terms of how well\, and how consistently\, they correlate with human evaluation scores (Over et al.\, 2007; Gatt and Belz\, 2008; Bojar et al.\, 2016; Shimorina\, 2018; Ma et al.\, 2019; Mille et al.\, 2019; Dušek et al.\, 2020). \nYet there is growing unease about how human evaluations are conducted in NLP. Researchers have pointed out the less than perfect experimental and reporting standards that prevail (van der Lee et al.\, 2019). Only a small proportion of papers provide enough detail for reproduction of human evaluations\, and in many cases the information provided is not even enough to support the conclusions drawn. More than 200 different quality criteria (Fluency\, Grammaticality\, etc.) have been used in NLP  (Howcroft et al.\, 2020). Different papers use the same quality criterion name with different definitions\, and the same definition with different names. As a result\, we currently do not have a way of determining whether two evaluations assess the same thing which poses problems for both meta-evaluation and reproducibility assessments (Belz et al.\, 2020). \nReproducibility in the context of automatically computed system scores has recently attracted a lot of attention\, against the background of a troubling history (Pedersen\, 2008; Mieskes et al.\, 2019)\, where reproduction is perceived as failing in 24.9% of cases for own results\, and in 56.7% for another team’s (Mieskes et al.\, 2019). Initiatives have included the Reproducibility Challenge (Pineau et al.\, 2019\, Sinha et al.\, 2020); the Reproduction Paper special category at COLING’18; the reproducibility programme at NeurIPS’19 comprising code submission\, a reproducibility challenge\, and the ML Reproducibility checklist\, also adopted by EMNLP’20 and AAAI’21; and the REPROLANG shared task at LREC’20 (Branco et al.\, 2020). \nHowever\, reproducibility in the context of system scores obtained via human evaluations has barely been addressed at all\, with a tiny number of papers (e.g. Belz & Kow\, 2010; Cooper & Shardlow\, 2020) reporting attempted reproductions of results. The developments in reproducibility of automatically computed scores listed above are important\, but it is concerning that not a single one of the initiatives and events above addresses human evaluations. E.g. if a paper fully complies with all of the NeurIPS’19/EMNLP’20 reproducibility criteria\, any human evaluation results reported in it may not be reproducible to any degree\, simply because the criteria do not address human evaluation in any way. \nWith this workshop we wish to create a forum for current human evaluation research and future directions\, a space for researchers working with human evaluations to exchange ideas and begin to address the issues that human evaluation in NLP currently faces\, including aspects of experimental design\, reporting standards\, meta-evaluation and reproducibility. We invite papers on topics including\, but not limited to\, the following: \n\n\nExperimental design for human evaluations \n\n\nReproducibility of human evaluations \n\n\nEthical considerations in human evaluation of computational systems \n\n\nQuality assurance for human evaluation \n\n\nCrowdsourcing for human evaluation \n\n\nIssues in meta-evaluation of automatic metrics by correlation with human evaluations \n\n\nAlternative forms of meta-evaluation and validation of human evaluations \n\n\nComparability of different human evaluations \n\n\nMethods for assessing the quality of human evaluations \n\n\nMethods for assessing the reliability of human evaluations \n\n\nWork on measuring inter-evaluator and intra-evaluator agreement \n\n\nFrameworks\, model cards and checklists for human evaluation \n\n\nExplorations of the role of human evaluation in the context of Responsible AI and Accountable AI \n\n\nProtocols for human evaluation experiments in NLP \n\n\nWe welcome work on the above topics and more from any subfield of NLP (and ML/AI more generally)\, with a particular focus on evaluation of systems that produce language as output. We explicitly encourage the submission of work on both intrinsic and extrinsic evaluation. \nPaper Submission Information\nLong Papers:\nLong papers must describe substantial\, original\, completed and unpublished work. Wherever appropriate\, concrete evaluation and analysis should be included. \nLong papers may consist of up to eight (8) pages of content\, plus unlimited pages of references. Final versions of long papers will be given one additional page of content (up to 9 pages) so that reviewers’ comments can be taken into account. \nLong papers will be presented orally or as posters as determined by the programme committee. Cecisions as to which papers will be presented orally and which as posters will be based on the nature rather than the quality of the work. There will be no distinction in the proceedings between long papers presented orally and as posters. \nShort Papers:\nShort paper submissions must describe original and unpublished work. Short papers should have a point that can be made in a few pages. Examples of short papers are a focused contribution\, a negative result\, an opinion piece\, an interesting application nugget\, a small set of interesting results. \nShort papers may consist of up to four (4) pages of content\, plus unlimited pages of references. Final versions of short papers will be given one additional page of content (up to 5 pages) so that reviewers’ comments can be taken into account. \nShort papers will be presented orally or as posters as determined by the programme committee. While short papers will be distinguished from long papers in the proceedings\, there will be no distinction in the proceedings between short papers presented orally and as posters. \nReview forms will be made available prior to the deadlines. For more information on applicable policies\, see the ACL Policies for Submission\, Review\, and Citation. \nMultiple Submission Policy\nHumEval’21 allows multiple submissions. However\, if a submission has already been\, or is planned to be\, submitted to another event\, this must be clearly stated in the submission \nEthics Policy\nAuthors are required to honour the ethical code set out in the ACL Code of Ethics. \nThe consideration of the ethical impact of our research\, use of data\, and potential applications of our work has always been an important consideration\, and as artificial intelligence is becoming more mainstream\, these issues are increasingly pertinent. We ask that all authors read the code\, and ensure that their work is conformant to this code. Where a paper may raise ethical issues\, we ask that you include in the paper an explicit discussion of these issues\, which will be taken into account in the review process. We reserve the right to reject papers on ethical grounds\, where the authors are judged to have operated counter to the ACL Code of Ethics\, or have inadequately addressed legitimate ethical concerns with their work. \nPaper Submission and Templates\nSubmission is electronic\, using the Softconf START conference management system. For electronic submission of all papers\, please use: https://www.softconf.com/eacl2021/HumEval2021. Both long and short papers must follow the ACL Author Guidelines\, and must use the EACL’21 templates. You can find the EACL-2021 LaTeX template here or download the zip file. \nOrganisers\n\nAnya Belz\, University of Brighton\, UK\nShubham Agarwal\, Heriot Watt University\, UK\nYvette Graham\, Trinity College Dublin\, Ireland\nEhud Reiter\, University of Aberdeen\nAnastasia Shimorina\, Université de Lorraine / LORIA\n\nPC Members\n\n\n\n\n\n\n\n\nMohit Bansal\, UNC Chapel Hill\, US \n\n\nSaad Mahamood\, Trivago\, DE \n\n\n\n\nKevin B. Cohen\, University of Colorado\, US \n\n\nNitika Mathur\, University of Melbourne\, Australia \n\n\n\n\nKees van Deemter\, Utrecht University\, NL \n\n\nMargot Mieskes\, UAS Darmstadt\, DE \n\n\n\n\nOndrej Dusek\, Charles University\, Czechia \n\n\nEmiel van Miltenburg\, Tilburg University\, NL \n\n\n\n\nKarën Fort\, Sorbonne University\, France \n\n\nMargaret Mitchell\, Google\, US \n\n\n\n\nAnette Frank\, University of Heidelberg\, DE \n\n\nMathias Mueller\, University of Zurich\, CH \n\n\n\n\nClaire Gardent\, CNRS/LORIA Nancy\, France \n\n\nMalvina Nissim\, Groningen University\, NL \n\n\n\n\nAlbert Gatt\, Malta University\, Malta \n\n\nJuri Opitz\, University of Heidelberg\, DE \n\n\n\n\nDimitra Gkatzia\, Edinburgh Napier University\, UK \n\n\nRamakanth Pasunuru\, UNC Chapel Hill\, US \n\n\n\n\nHelen Hastie\, Heriot-Watt University\, UK \n\n\nMaxime Peyrard\, EPFL\, CH \n\n\n\n\nDavid Howcroft\, Heriot Watt University\, UK \n\n\nInioluwa Deborah Raji\, Ai Now Institute\, US \n\n\n\n\nJackie Chi Kit Cheung\, McGill University\, Canada \n\n\nVerena Rieser\, Heriot Watt University\, UK \n\n\n\n\nSamuel Läubli\, University of Zurich\, CH \n\n\nSamira Shaikh\, UNC\, US \n\n\n\n\nChris van der Lee\, Tilburg University\, NL \n\n\nLucia Specia\, UCL\, UK \n\n\n\n\nNelson Liu\, Washington University\, US \n\n\nWei Zhao\, TU Darmstadt\, DE \n\n\n\n\nQun Liu\, Huawei Noah’s Ark Lab\, China \n\n\n\n\n\n\nContact Information\nhumeval.ws@gmail.com \nhttps://humeval.github.io
URL:https://www.loria.fr/event/workshop-on-human-evaluation-of-nlp-systems-humeval/
CATEGORIES:Séminaire
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Paris:20210420T133000
DTEND;TZID=Europe/Paris:20210420T150000
DTSTAMP:20260519T161142
CREATED:20210409T101721Z
LAST-MODIFIED:20210409T120947Z
UID:12004-1618925400-1618930800@www.loria.fr
SUMMARY:Colloquium Loria - CELLO Team
DESCRIPTION:Next Colloquium will take place on Tuesday\, 20th April at 1:30 pm on Teams. \nWe are glad to welcome the CELLO team\, with presentations given by our colleagues Hans van Ditmarsch\, Marta Gawek and Mo Liu. \n \n\nProgram and abstracts: \n13:30 – 14:00 \n\nspeaker: Hans van Ditmarsch\, CELLO @ LORIA\ntitle: Knowledge and simplicial complexes\nabstract: Simplicial complexes are a versatile and convenient paradigm on which to build all the tools and techniques of the logic of knowledge\, on the assumption that initial epistemic models can be described in a distributed fashion. Thus\, we can define: knowledge\, belief\, bisimulation\, the group notions of mutual\, distributed and common knowledge\, and also dynamics in the shape of simplicial action models. We give a survey on how to interpret all such notions on simplicial complexes\, building upon the foundations laid in prior work by Goubault et al. More recent work investigates so-called impure simplicial complexes\, that also take into account crashed processes.\nReferences:\n[1] Hans van Ditmarsch\, Eric Goubault\, Jérémy Ledent\, and Sergio Rajsbaum. Knowledge and simplicial complexes. To appear. CoRR abs/2002.08863\, 2020.\n[2] Hans van Ditmarsch. Wanted Dead or Alive: Epistemic logic for impure simplicial complexes. CoRR abs/2103.03032\, 2021.\n\n        Joint work with Éric Goubault\, Jérémy Ledent\, and Sergio Rajsbaum. \n\n\n  \n14:00 – 14:30 \n\nspeaker: Marta Gawek\, CELLO @ LORIA\ntitle: An epistemic separation logic with action models\nabstract: We investigate extensions of separation logic with epistemic and dynamic epistemic modalities. Separation logics are based on the intuitionistic logic of bunched implications (BI) or its classical counterpart Boolean BI. These logics combine additive and multiplicative connectives in the language\, expressing the notions of resource composition and resource decomposition. Epistemic Separation Logic with Action Models (ESLAM) is a generalization of the Public Announcement Separation Logic (PASL) of Courtault et al. We present the syntax and semantics of ESLAM as well as reduction axioms for the elimination of dynamic modalities.\nReferences: [1] Jean-René Courtault\, Hans van Ditmarsch\, and Didier Galmiche. A Public Announcement Separation Logic. Mathematical Structures in Computer Science 29(6):828–871\, 2019.\n[2] David Pym. The Semantics and Proof Theory of the Logic of Bunched Implications\, Springer\, 2002.\n[3] Hans van Ditmarsch\, Didier Galmiche\, and Marta Gawek. An Epistemic Separation Logic with Action Models. Proceedings of 9th ICLA\, 2021.Joint work with Hans van Ditmarsch and Didier Galmiche.\n\n\n14:30 – 15:00 \n\nspeaker: Mo Liu\, CELLO @ LORIA\ntitle: Expressivity of some versions of APAL\nabstract: Arbitrary public announcement logic (APAL) is a logic of change of knowledge with   modalities representing quantification over announcements. It extends public announcement logic (PAL). We present three rather different versions of APAL: FSAPAL only quantifies over announcements containing a finite subset of all propositional variables. SCAPAL only quantifies over announcements containing variables occurring in the formula bound by the quantifier. IPAL quantifies over announcements implying a given formula. We determine the relative expressivity of FSAPAL\, SCAPAL and IPAL in relation to APAL and PAL.\nReferences:\n[1] Hans van Ditmarsch\, Mo Liu\, Louwe B. Kuijer\, and Igor Sedlár. Expressivity of Some Versions of APAL. Proceedings of DaLí 2020\, pp 120-136\, 2020.\n\n\n        Joint work with Hans van Ditmarsch\, Louwe B. Kuijer\, and Igor Sedlár.
URL:https://www.loria.fr/event/12004/
LOCATION:online
CATEGORIES:Colloquium Loria
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Paris:20210422T093000
DTEND;TZID=Europe/Paris:20210422T113000
DTSTAMP:20260519T161142
CREATED:20210421T140948Z
LAST-MODIFIED:20210421T141126Z
UID:12149-1619083800-1619091000@www.loria.fr
SUMMARY:PhD defense: Mingxiao Ma
DESCRIPTION:Mingxiao Ma (RESIST) will defend his thesis\, entitled “Attack Modelling and Detection in Distributed and Cooperative Controlled Microgrid Systems“. The defense will be held online and it will take place on Thursday\, 22 April 2021 at 9:30 am. \n\n\nAbstract \n\nModern low-voltage microgrid systems rely on distributed and cooperative control approaches to guarantee safe and reliable operational decisions of their inverter-based distributed generators (DGs). However\, many sophisticated cyber-attacks can target these systems\, deceive their traditional detection methods and cause a severe impact on the power infrastructure.\n\nIn this thesis\, we systematically study the vulnerabilities and threats of distributed controlled microgrid systems. We design a novel attack named “measurement-as-reference” (MaR) attack and take it as a typical stealthy attack example to theoretically analyze the attack impact on the microgrid system and use numerical simulation results to verify the analysis. We provide mathematical models of possible false data injection (FDI) and denial of service (DoS) attacks in a representative distributed and cooperative controlled microgrid system. We propose a secure control framework with an attack detection module based on machine learning techniques. To validate the effectiveness of this framework\, we implement two typical attacks\, MaR attack and delay injection attack\, on a hardware platform modeled after a microgrid system. We collect datasets from the platform and validate the performance of multiple categories of machine learning algorithms to detect such attacks. Our results show that tree-based classifiers (Decision Tree\, Random Forest and AdaBoost) outperform other algorithms and achieve excellent performance in detecting normal behavior\, delay injection and false data attacks.\n\n\n\nComposition of jury:\nReviewers :\n                       Mohamed Kaâniche: Directeur de recherche CNRS au LAAS\, France\n                       Stéphane Mocanu: Maître de conférences à Université de Grenoble-Alpes\, France\n\n\nExaminers : \n\n                       Ghita Mezzour: Maître de conférences à Université Internationale de Rabat\, Maroc\n                       Abdelmadjid Bouabdallah: Professeur à Université de Technologie de Compiègne\, France\n                       Ye-Qiong Song: Professeur à Université de Lorraine\, France\n\nSupervisors :\n                      Isabelle Chrisment: Professeure à Télécom Nancy\, Nancy \, France\n                      Abdelkader Lahmadi: Maître de conférences à Université de Lorraine\, France
URL:https://www.loria.fr/event/phd-defense-mingxiao-ma/
CATEGORIES:Soutenance
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Paris:20210423T140000
DTEND;TZID=Europe/Paris:20210423T160000
DTSTAMP:20260519T161142
CREATED:20210421T135352Z
LAST-MODIFIED:20210421T135352Z
UID:12147-1619186400-1619193600@www.loria.fr
SUMMARY:PhD defense: Bishnu Sarker
DESCRIPTION:Bishnu Sarker (CAPSID) will defend his thesis\, entitled : On Graph-based Approaches for Protein Function Annotation and Knowledge Discovery. The defense will take place on Friday\, 23 April 2021 at 14:00. Due to the health situation\, the defense will be held online. \nAbstract \nDue to the recent advancement in genomic sequencing technologies\, the number of protein entries in public databases is growing exponentially. It is important to harness this huge amount of data to describe living things at the molecular level\, which is essential for understanding human disease processes and accelerating drug discovery. A prerequisite\, however\, is that all of these proteins be annotated with functional properties such as Enzyme Commission (EC) numbers and Gene Ontology (GO) terms. Today\, only a small fraction of the proteins is functionally annotated and reviewed by expert curators because it is expensive\, slow and time-consuming. Developing automatic protein function annotation tools is the way forward to reduce the gap between the annotated and unannotated proteins and to predict reliable annotations for unknown proteins. Many tools of this type already exist\, but none of them are fully satisfactory. We observed that only few consider graph-based approaches and the domain composition of proteins. Indeed\, domains are conserved regions across protein sequences of the same family. In this thesis\, we design and evaluate graph-based approaches to perform automatic protein function annotation and we explore the impact of domain architecture on protein functions. The first part is dedicated to protein function annotation using domain similarity graph and neighborhood-based label propagation technique. we present GrAPFI (Graph-based Automatic Protein Function Inference) for automatically annotating proteins with enzymatic functions (EC numbers) and GO terms from a protein-domain similarity graph. We validate the performance of GrAPFI using six reference proteomes from UniprotKB/SwissProt and compare GrAPFI results with state-of-the-art EC prediction approaches. We find that GrAPFI achieves better accuracy and comparable or better coverage. The second part of the dissertation deals with learning representation for biological entities. At the beginning\, we focus on neural network-based word embedding technique. We formulate the annotation task as a text classification task. We build a corpus of proteins as sentences composed of respective domains and learn fixed dimensional vector representation for proteins. Then\, we focus on learning representation from heterogeneous biological network. We build knowledge graph integrating different sources of information related to proteins and their functions. We formulate the problem of function annotation as a link prediction task between proteins and GO terms. We propose Prot-A-GAN\, a machine-learning model inspired by Generative Adversarial Network (GAN) to learn vector representation of biological entities from protein knowledge graph. We observe that Prot-A-GAN works with promising results to associate appropriate functions with query proteins. In conclusion\, this thesis revisits the crucial problem of large-scale automatic protein function annotation in the light of innovative techniques of artificial intelligence. It opens up wide perspectives\, in particular for the use of knowledge graphs\, which are today available in many fields other than protein annotation thanks to the progress of data science.\n\n\nComposition of jury:\nReviewers :\n                       Christine Brun : Research Director\,  CNRS\, Inserm-University of Marseille\, France.\n                       Mohamed Elati : Professor\, University of Lille\, France. \n\nExaminers :\n                       Anne Boyer : Professor\, University of  Lorraine\, France.\n                       Albert Montresor : Professor\, University of Trento\, Italy.\n\n\nSupervisors :\n                      David W. Ritchie (till Sept 2019) : Research Director\, Inria\, Nancy\, France.\n                      Marie-Dominique Devignes (from sept 2019) : Associate Researcher\, CNRS\, Nancy\, France.\n                      Sabeur Aridhi : Associate Professor\, University of Lorraine\, France.
URL:https://www.loria.fr/event/phd-defense-bishnu-sarker/
LOCATION:Teams
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DTSTART;TZID=Europe/Paris:20210423T150000
DTEND;TZID=Europe/Paris:20210423T163000
DTSTAMP:20260519T161142
CREATED:20210416T094459Z
LAST-MODIFIED:20210416T094508Z
UID:12079-1619190000-1619195400@www.loria.fr
SUMMARY:HDR defense - Claudia Ignat (Coast)
DESCRIPTION:Claudia Ignat (Coast team) will defend her HDR (Habilitation à Diriger des Recherches)\, entitled “Large-scale trustworthy distributed collaborative systems” on Friday April 23 at 3pm. The defense will be held in English. \n \nShort abstract: \nMost existing collaborative systems rely on a central authority and place personal information in the hands of a single large corporation which is a perceived privacy threat. Moreover\, these systems do not scale well in terms of the number of users and their modifications. My research work aims to move away from centralized authority-based collaboration towards a large scale trust-based peer-to-peer collaboration where control over data is given to users who can decide with whom to share their data. The main advantages of peer-to-peer collaborative systems are high scalability and resilience to faults and attacks. \nFirst\, I describe my contributions to the design and evaluation of optimistic data replication algorithms. I also present my work on group awareness specifically on what information should be provided to users to prevent conflicting changes and to understand divergence when conflicts cannot be avoided. \nSecondly\, I describe my contributions on large scale trustworthy collaboration. I present a contract-based collaboration model where contracts are specified by the data owners when they share the data and user trust is assessed according to the observation of adherence to or violation of contracts. For testing the proposed trust-based collaboration model\, I designed a user experiment employing trust game and relying on a computational trust metric according to user exchanges in this game. \nFinally\, I present my future research directions on secure and trustworthy collaborative data management. \nKeywords: distributed collaborative systems\, operational transformation\, CRDT\, group awareness\, trust\, contract-based collaboration\, authenticated logs\, trust game\, user studies \nMore details are available here \nJury members\nReviewers\nPrasun DEWAN\, Professor at University of North Carolina at Chapel Hill\nValerie ISSARNY\, Director of research at Inria\nFrançois TAIANI\, Professor at Université de Rennes I \nExaminers\nSihem AMER-YAHIA\, Director of research at CNRS\nFrançois CHAROY\, Professor at Université de Lorraine\nIsabelle CHRISMENT\, Professor at Université de Lorraine\nFabien GANDON\, Director of research at Inria\nPascal MOLLI\, Professor at Université de Nantes
URL:https://www.loria.fr/event/habilitation-defense-claudia-ignat-coast/
CATEGORIES:HDR
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