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Rémi Bardenet
87
Documents
Publications
Smoothing complex-valued signals on Graphs with Monte-CarloICASSP 2023 - IEEE International Conference on Acoustics, Speech and Signal Processing, Jun 2023, Rhodes Island, Greece. ⟨10.1109/ICASSP49357.2023.10096354⟩
Conference papers
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Estimation de la fonction de structure d'un processus ponctuel pour l'étude d'hyperuniformitéXXVIIIème Colloque Francophone de Traitement du Signal et des Images GRETSI 2022, Sep 2022, Nancy, France
Conference papers
hal-03747149v1
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A public benchmark for denoising and detection methodsXXVIIIème Colloque Francophone du GRETSI, GRETSI, Sep 2022, Nancy, France. pp.1-4
Conference papers
hal-04102094v1
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Nonparametric estimation of continuous DPPs with kernel methodsNeurIPS 2021 - Thirty-fifth Conference on Neural Information Processing Systems, 2021, Virtual event, Turkmenistan
Conference papers
hal-03368398v1
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Determinantal point processes based on orthogonal polynomials for sampling minibatches in SGDNeurIPS 2021 - Thirty-fifth Conference on Neural Information Processing Systems,, 2021, Virtual event, Turkmenistan
Conference papers
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Kernel interpolation with continuous volume samplingICML 2020 - International Conference on Machine Learning, 2020, Vienna, Austria
Conference papers
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Un processus ponctuel déterminantal pour la sélection d'attributsGRETSI 2019, Aug 2019, Lille, France
Conference papers
hal-02439935v1
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On two ways to use determinantal point processes for Monte Carlo integrationNEGDEPML 2019 - ICML Workshop on Negative Dependence in ML, Jun 2019, Long Beach, CA, United States
Conference papers
hal-02160382v1
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Kernel quadrature with DPPsNeurIPS 2019 - Thirty-third Conference on Neural Information Processing Systems, Jun 2019, Vancouver, Canada
Conference papers
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A correspondence between zeros of time-frequency transforms and Gaussian analytic functions13th International Conference on Sampling Theory and Applications, SampTA 2019, Aug 2019, Bordeaux, France
Conference papers
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On two ways to use determinantal point processes for Monte Carlo integration -- Long versionNeurIPS 2019 - Thirty-third Conference on Neural Information Processing Systems, Jun 2019, Vancouver, Canada
Conference papers
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From random matrices to Monte Carlo integration via Gaussian quadratureIEEE Statistical Signal processing workshop, 2018, Freiburg, Germany
Conference papers
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Zonotope hit-and-run for efficient sampling from projection DPPsInternational Conference on Machine Learning, 2017, Sydney, Australia
Conference papers
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Inference for determinantal point processes without spectral knowledgeNeural Information Processing Systems (NIPS), Dec 2015, Montréal, Canada
Conference papers
hal-01245315v1
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Towards scaling up Markov chain Monte Carlo: an adaptive subsampling approachInternational Conference on Machine Learning (ICML), 2014, Beijing, China. pp.405-413
Conference papers
hal-01254232v1
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Highlights from the Pierre Auger Observatory33rd International Cosmic Ray Conference (ICRC2013), Jul 2013, Rio de Janeiro, Brazil
Conference papers
in2p3-00923571v1
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Detection and estimation of high energy physical particles using Monte Carlo methodsColloque du GRETSI, Sep 2013, Brest, France
Conference papers
hal-02287064v1
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Collaborative hyperparameter tuning30th International Conference on Machine Learning (ICML 2013), Jun 2013, Atlanta, United States. pp.199-207
Conference papers
in2p3-00907381v1
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Adaptive Metropolis with online relabelingFifteenth International Conference on Artificial Intelligence and Statistics, Apr 2012, La Palma, Spain. pp.91-99
Conference papers
in2p3-00698479v1
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Monte Carlo methodsIN2P3 School of Statistics (SOS2012), May 2012, Autrans, France. pp.022002, ⟨10.1051/epjconf/20135502002⟩
Conference papers
in2p3-00846142v1
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The Pierre Auger Observatory II: Studies of Cosmic Ray Composition and Hadronic Interaction models32nd International Cosmic Ray Conference - ICRC 2011, 2011, Beijing, China
Conference papers
in2p3-00630600v1
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The Pierre Auger Observatory III: Other Astrophysical Observations32nd International Cosmic Ray Conference - ICRC 2011, 2011, Beijing, China
Conference papers
in2p3-00630613v1
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An adaptive Monte-Carlo Markov chain algorithm for inference from mixture signals14th International Workshop on Advanced Computing and Analysis Techniques in Physics Research (ACAT 2011), Sep 2011, Uxbridge, United Kingdom. pp.012044, ⟨10.1088/1742-6596/368/1/012044⟩
Conference papers
in2p3-00714497v1
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The Pierre Auger Observatory I: The Cosmic Ray Energy Spectrum and Related Measurements32nd International Cosmic Ray Conference (ICRC2011), 2011, Beijing, China
Conference papers
in2p3-00616470v1
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The Pierre Auger Observatory V: Enhancements32nd International Cosmic Ray Conference (ICRC2011), Aug 2011, Beijing, China
Conference papers
in2p3-00616493v1
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Algorithms for Hyper-Parameter Optimization25th Annual Conference on Neural Information Processing Systems (NIPS 2011), Dec 2011, Granada, Spain
Conference papers
hal-00642998v1
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The Pierre Auger Observatory IV: Operation and Monitoring32nd International Cosmic Ray Conference - ICRC 2011, 2011, Beijing, China
Conference papers
in2p3-00630621v1
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Surrogating the surrogate: accelerating Gaussian-process-based global optimization with a mixture cross-entropy algorithm27th International Conference on Machine Learning (ICML 2010), Jun 2010, Haifa, Israel. pp.55-62
Conference papers
in2p3-00580438v1
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Relabelling MCMC Algorithms in Bayesian Mixture LearningSnowbird Learning Workshop, Apr 2011, Fort Lauderdale, United States
Conference poster
in2p3-00590956v1
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Sampling-based optimization with mixturesOPT 2009: 2nd NIPS Workshop on Optimization for Machine Learning, Dec 2009, Whistler, Canada
Conference poster
in2p3-00580580v1
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Towards adaptive learning and inference - Applications to hyperparameter tuning and astroparticle physicsMethodology [stat.ME]. Université Paris Sud - Paris XI, 2012. English. ⟨NNT : ⟩
Theses
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