يعرض 1 - 10 نتائج من 17 نتيجة بحث عن '"Florian Strub"', وقت الاستعلام: 1.00s تنقيح النتائج
  1. 1
    Mastering the Game of Stratego with Model-Free Multiagent Reinforcement Learning

    المؤلفون: Julien Perolat, Bart De Vylder, Daniel Hennes, Eugene Tarassov, Florian Strub, Vincent de Boer, Paul Muller, Jerome T. Connor, Neil Burch, Thomas Anthony, Stephen McAleer, Romuald Elie, Sarah H. Cen, Zhe Wang, Audrunas Gruslys, Aleksandra Malysheva, Mina Khan, Sherjil Ozair, Finbarr Timbers, Toby Pohlen, Tom Eccles, Mark Rowland, Marc Lanctot, Jean-Baptiste Lespiau, Bilal Piot, Shayegan Omidshafiei, Edward Lockhart, Laurent Sifre, Nathalie Beauguerlange, Remi Munos, David Silver, Satinder Singh, Demis Hassabis, Karl Tuyls

    مصطلحات موضوعية: FOS: Computer and information sciences, Artificial Intelligence (cs.AI), Multidisciplinary, Video Games, Artificial Intelligence, Computer Science - Artificial Intelligence, Computer Science - Computer Science and Game Theory, Humans, Computer Science - Multiagent Systems, Reinforcement, Psychology, Computer Science and Game Theory (cs.GT), Multiagent Systems (cs.MA)

    URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::43318777c84d87510982d653d787e4b1
    http://arxiv.org/abs/2206.15378

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  2. 2
    Learning Natural Language Generation with Truncated Reinforcement Learning

    المؤلفون: Alice Martin, Guillaume Quispe, Charles Ollion, Sylvain Le Corff, Florian Strub, Olivier Pietquin

    المصدر: Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies.

    URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_________::3c22a15ff8f701fd2e0e5eebaa1b92f2
    https://doi.org/10.18653/v1/2022.naacl-main.2

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  3. 3
    Developing, Evaluating and Scaling Learning Agents in Multi-Agent Environments

    المؤلفون: Ian Gemp, Thomas Anthony, Yoram Bachrach, Avishkar Bhoopchand, Kalesha Bullard, Jerome Connor, Vibhavari Dasagi, Bart De Vylder, Edgar A. Duéñez-Guzmán, Romuald Elie, Richard Everett, Daniel Hennes, Edward Hughes, Mina Khan, Marc Lanctot, Kate Larson, Guy Lever, Siqi Liu, Luke Marris, Kevin R. McKee, Paul Muller, Julien Pérolat, Florian Strub, Andrea Tacchetti, Eugene Tarassov, Zhe Wang, Karl Tuyls

    مصطلحات موضوعية: FOS: Computer and information sciences, Artificial Intelligence (cs.AI), Artificial Intelligence, Computer Science - Artificial Intelligence, Computer Science - Multiagent Systems, Multiagent Systems (cs.MA)

    URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::89b3dc7eea201bf0030a0f62b9dbd4d9

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  4. 4
    Broaden Your Views for Self-Supervised Video Learning

    المؤلفون: Adria Recasens, Pauline Luc, Jean-Baptiste Alayrac, Luyu Wang, Florian Strub, Corentin Tallec, Mateusz Malinowski, Viorica Patraaucean, Florent Altche, Michal Valko, Jean-Bastien Grill, Aaron van den Oord, Andrew Zisserman

    المصدر: 2021 IEEE/CVF International Conference on Computer Vision (ICCV).

    URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_________::8e0bab174bbf0c9c5ec0dc2321138cfc
    https://doi.org/10.1109/iccv48922.2021.00129

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  5. 5
    Don’t Do What Doesn’t Matter: Intrinsic Motivation with Action Usefulness

    المؤلفون: Florian Strub, Mathieu Seurin, Philippe Preux, Olivier Pietquin

    المصدر: IJCAI

    مصطلحات موضوعية: Action (philosophy), Computer science, Salient, Human–computer interaction, Novelty, State space, Reinforcement learning, Exploration problem, State (computer science), Object (philosophy)

    URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_________::d8a1b3b5298953be08fc2c37e6dba88b
    https://doi.org/10.24963/ijcai.2021/406

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  6. 6
    Supervised Seeded Iterated Learning for Interactive Language Learning

    المؤلفون: Aaron Courville, Olivier Pietquin, Yuchen Lu, Soumye Singhal, Florian Strub

    المصدر: EMNLP (1)

    مصطلحات موضوعية: FOS: Computer and information sciences, Computer Science - Computation and Language, business.industry, Computer science, 02 engineering and technology, 010501 environmental sciences, Language acquisition, computer.software_genre, 01 natural sciences, Task (project management), Dynamics (music), Iterated learning, 0202 electrical engineering, electronic engineering, information engineering, 020201 artificial intelligence & image processing, Artificial intelligence, Language model, business, computer, Computation and Language (cs.CL), Word (computer architecture), Natural language, Natural language processing, 0105 earth and related environmental sciences

    URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8e42e3656072de738d074635ff15ecbc
    http://arxiv.org/abs/2010.02975

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  7. 7
    HIGhER: Improving instruction following with Hindsight Generation for Experience Replay

    المؤلفون: Florian Strub, Geoffrey Cideron, Mathieu Seurin, Olivier Pietquin

    المساهمون: Seurin, Mathieu, Child-Robot Communication and Collaboration: Edutainment, Behavioural Modelling and Cognitive Development in Typically Developing and Autistic Spectrum Children - BabyRobot - - H20202016-01-01 - 2018-12-31 - 687831 - VALID, Ecole Normale Supérieure Paris-Saclay (ENS Paris Saclay), Scool (Scool), Inria Lille - Nord Europe, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 (CRIStAL), Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS), DeepMind [Paris], Google Research [Paris], European Project: 687831,H2020,H2020-ICT-2015,BabyRobot(2016)

    المصدر: SSCI
    ADPRL 2020-IEEE SSCI Conference on Adaptive Dynamic Programming and Reinforcement Learning
    ADPRL 2020-IEEE SSCI Conference on Adaptive Dynamic Programming and Reinforcement Learning, Dec 2020, Camberra / Virtual, Australia

    مصطلحات موضوعية: FOS: Computer and information sciences, [INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI], Computer Science - Machine Learning, Principle of compositionality, Computer science, Machine Learning (stat.ML), Representation Learning, 010501 environmental sciences, 01 natural sciences, Structuring, 050105 experimental psychology, Machine Learning (cs.LG), [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI], Statistics - Machine Learning, Human–computer interaction, Reinforcement learning, 0501 psychology and cognitive sciences, 0105 earth and related environmental sciences, Natural Language Processing, Computer Science - Computation and Language, 05 social sciences, Reinforcement Learning, Visualization, Task analysis, State (computer science), Computation and Language (cs.CL), Feature learning, Hindsight bias

    وصف الملف: application/pdf

    URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::10ca21396c8c801207e63fed731b6541
    https://hal.science/hal-03123981

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  8. 8
    A Machine of Few Words -- Interactive Speaker Recognition with Reinforcement Learning

    المؤلفون: Philippe Preux, Florian Strub, Olivier Pietquin, Mathieu Seurin

    المساهمون: Scool (Scool), Inria Lille - Nord Europe, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 (CRIStAL), Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS), Sequential Learning (SEQUEL), Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 (CRIStAL), Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS), Université de Lille, DeepMind [Paris], Google Research [Paris]

    المصدر: Interspeech 2020 proceedings
    Conference of the International Speech Communication Association (INTERSPEECH)
    Conference of the International Speech Communication Association (INTERSPEECH), Oct 2020, Shanghai, China. ⟨10.21437/Interspeech.2020-2892⟩
    INTERSPEECH

    مصطلحات موضوعية: FOS: Computer and information sciences, Computer Science - Machine Learning, reinforcement learning, Sound (cs.SD), Computer science, 020209 energy, Speech recognition, Speech synthesis, 02 engineering and technology, iterative representation learning, computer.software_genre, Computer Science - Sound, Task (project management), Domain (software engineering), [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI], Machine Learning (cs.LG), [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG], [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, Audio and Speech Processing (eess.AS), 0202 electrical engineering, electronic engineering, information engineering, FOS: Electrical engineering, electronic engineering, information engineering, Reinforcement learning, [INFO]Computer Science [cs], business.industry, Deep learning, deep learning, Speaker recognition, Speech processing, active speaker recognition, 020201 artificial intelligence & image processing, Artificial intelligence, business, computer, Utterance, Electrical Engineering and Systems Science - Audio and Speech Processing

    URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b5848db0e26f12c2ac1c2ae4796e9e6c

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  9. 9
    Accurate reconstruction of EBSD datasets by a multimodal data approach using an evolutionary algorithm

    المؤلفون: Florian Strub, Marie-Agathe Charpagne, Tresa M. Pollock

    المساهمون: University of California [Santa Barbara] (UCSB), University of California, Sequential Learning (SEQUEL), Inria Lille - Nord Europe, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 (CRIStAL), Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS), Université de Lille, Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 (CRIStAL), Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS), University of California [Santa Barbara] (UC Santa Barbara), University of California (UC)

    المصدر: Materials Characterization
    Materials Characterization, Elsevier, 2019, 150, pp.184-198. ⟨10.1016/j.matchar.2019.01.033⟩
    Materials Characterization, 2019, 150, pp.184-198. ⟨10.1016/j.matchar.2019.01.033⟩

    مصطلحات موضوعية: FOS: Computer and information sciences, Materials science, Physics - Instrumentation and Detectors, EBSD, FOS: Physical sciences, 02 engineering and technology, [INFO.INFO-NE]Computer Science [cs]/Neural and Evolutionary Computing [cs.NE], 01 natural sciences, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI], Speckle pattern, Distortion, 0103 physical sciences, General Materials Science, Neural and Evolutionary Computing (cs.NE), CMA-ES, 010302 applied physics, Distortion function, Image segmentation, Pixel, Multi-modal data, Mechanical Engineering, Distortions, Computer Science - Neural and Evolutionary Computing, Instrumentation and Detectors (physics.ins-det), 021001 nanoscience & nanotechnology, Condensed Matter Physics, Transformation (function), Mechanics of Materials, Feature (computer vision), Physics - Data Analysis, Statistics and Probability, 0210 nano-technology, Algorithm, Data Analysis, Statistics and Probability (physics.data-an)

    URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b8db8e7cae072030a15c06a24aab900a

    View record from ScienceDirect
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  10. 10
    Visual Reasoning with Multi-hop Feature Modulation

    المؤلفون: Florian Strub, Harm de Vries, Philippe Preux, Olivier Pietquin, Aaron Courville, Ethan Perez, Mathieu Seurin, Jérémie Mary

    المساهمون: Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 (CRIStAL), Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS), Université de Lille, Sequential Learning (SEQUEL), Inria Lille - Nord Europe, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 (CRIStAL), Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS), Rice University [Houston], Department of Computer Science and Operations Research [Montreal], Montreal Institute for Learning Algorithms [Montréal] (MILA), Centre de Recherches Mathématiques [Montréal] (CRM), Université de Montréal (UdeM)-Université de Montréal (UdeM), Criteo [Paris], CIFAR, Google Inc, Research at Google, CPER Nord-Pas de Calais/FEDER DATA Advanced data science and technologies 2015-2020, NSERC, Calcul Québec, Compute Canada, The Canada Research Chairs, Vittorio Ferrari, Martial Hebert, Cristian Sminchisescu, Yair Weiss, European Project: 687831,H2020,H2020-ICT-2015,BabyRobot(2016), European Project: IGLU

    المصدر: ECCV 2018-15th European Conference on Computer Vision
    ECCV 2018-15th European Conference on Computer Vision, Sep 2018, Munich, Germany. pp.808-831
    Computer Vision – ECCV 2018 ISBN: 9783030012274
    ECCV (5)

    مصطلحات موضوعية: FOS: Computer and information sciences, Computer Science - Machine Learning, Computer science, Natural Language Understanding, Computer Vision and Pattern Recognition (cs.CV), Speech recognition, Computer Vision, Computer Science - Computer Vision and Pattern Recognition, Natural language understanding, Machine Learning (stat.ML), 02 engineering and technology, 010501 environmental sciences, [INFO.INFO-NE]Computer Science [cs]/Neural and Evolutionary Computing [cs.NE], computer.software_genre, 01 natural sciences, Machine Learning (cs.LG), [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI], Qualitative analysis, Deep Learning, [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG], Statistics - Machine Learning, 0202 electrical engineering, electronic engineering, information engineering, Multi-modal Learning, 0105 earth and related environmental sciences, Computer Science - Computation and Language, business.industry, Deep learning, [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], Visual reasoning, 020201 artificial intelligence & image processing, Artificial intelligence, business, Computation and Language (cs.CL), computer, Natural language

    URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::34b3312b9ed95d2f3197c78c2827505a
    https://hal.archives-ouvertes.fr/hal-01927811

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