Joon Kwon

Publications

Article dans une revue (7)

Data paper: A goat behaviour dataset combining labelled behaviours and accelerometer data for training Machine Learning detection models Sarah Mauny,Joon Kwon,Nicolas N.C. Friggens,Christine Duvaux-Ponter,Masoomeh Taghipoor Animal - Open Space, 2025, 4, pp.100095. ⟨10.1016/j.anopes.2025.100095⟩ Article dans une revue (data paper) hal-04997560v1
Importance sampling-based gradient method for dimension reduction in Poisson log-normal model Bastien Batardière,Julien Chiquet,Joon Kwon,Julien Stoehr Electronic Journal of Statistics , 2025, 19 (1), ⟨10.1214/25-EJS2384⟩ Article dans une revue hal-04712554v4
A pipeline with pre-processing options to detect behaviour from accelerometer data using Machine Learning tested on dairy goats Sarah Mauny,Joon Kwon,Nicolas N.C. Friggens,Christine Duvaux-Ponter,Masoomeh Taghipoor Peer Community Journal, 2025, 5, pp.e41. ⟨10.24072/pcjournal.545⟩ Article dans une revue hal-05122302v1
Refined approachability algorithms and application to regret minimization with global costs Joon Kwon Journal of Machine Learning Research, 2021, 22, pp.1-38 Article dans une revue hal-04217335v1
A continuous-time approach to online optimization Joon Kwon,Panayotis Mertikopoulos Journal of Dynamics and Games, 2017, 4 (2), pp.125-148. ⟨10.3934/jdg.2017008⟩ Article dans une revue hal-02619471v1
A universal bound on the variations of bounded convex functions Joon Kwon Journal of Convex Analysis, 2017, 24 (1), pp.67-73 Article dans une revue hal-02618650v1
Gains and losses are fundamentally different in regret minimization: the sparse case Joon Kwon,Vianney Perchet Journal of Machine Learning Research, 2016, 17 (227), pp.1-32 Article dans une revue hal-02630070v1

Communication dans un congrès (5)

Benchmarking predictive models: evaluating parametric, ensemble, and deep learning approaches for animal phenotype prediction from genotypes. Eric Barrey,Blaise Hanczar,Julien Chiquet,Didier Boichard,Jocelyn de Goër de Herveet al. AI and biology Symposium, EMBO EMBL, Heidelberg, Mar 2024, Heidelberg, Germany Communication dans un congrès hal-04510253v1
Sparse stochastic bandits Joon Kwon,Vianney Perchet,Claire Vernade 2017 Conference on Learning Theory (COLT), Jul 2017, Amsterdam, Netherlands Communication dans un congrès hal-02734034v1
Sparse Stochastic Bandits Joon Kwon,Vianney Perchet,Claire Vernade COLT, May 2017, Amsterdam, Netherlands Communication dans un congrès hal-02287913v1
Sparse Stochastic Bandits Joon Kwon,Vianney Perchet,Claire Vernade Conference on Learning Theory, Jul 2017, Amsterdam, Netherlands Communication dans un congrès hal-03089519v1
Online learning and Blackwell approachability with partial monitoring: optimal convergence rates Joon Kwon,Vianney Perchet 20. International Conference on Artificial Intelligence and Statistics (AISTATS), Apr 2017, Fort Lauderdale, United States Communication dans un congrès hal-02734035v1

Poster de conférence (2)

Évaluation intégrée du bien-être positif chez les chèvres laitières : Une première étude expérimentale combinant approches éthologiques et numériques Mathilde Valenchon,Sarah Mauny,Chloé Deneuville,Pauline Gauthier,Alexandra Eymardet al. Journées scientifiques 2025 du PEPR Agroécologie et Numérique, Jan 2025, Dijon, France Poster de conférence hal-05261697v1
Analysis of dairy cows’ activity using a hybrid modelling approach for the early detection of health problems Masoomeh Taghipoor,Séverine Bord,Quentin Bulk,Joon Kwon UFAW 2022 - Advancing Animal Welfare Science, Jun 2022, Edinburgh, United Kingdom Poster de conférence hal-03776962v1

Pré-publication, Document de travail (4)

Finite-sum optimization: Adaptivity to smoothness and loopless variance reduction Bastien Batardière,Julien Chiquet,Joon Kwon 2023 Pré-publication, Document de travail hal-04217357v1
Global Plant Extinction Risk Assessment Inform Novel Biodiversity Hotspots Thomas Haevermans,Jessica Tressou,Joon Kwon,Roseli Pellens,Anne Dubéarnèset al. 2023 Pré-publication, Document de travail hal-04217346v1
A MOM-based ensemble method for robustness, subsampling and hyperparameter tuning Joon Kwon,Matthieu Lerasle,Guillaume Lecué 2019 Pré-publication, Document de travail hal-02786143v1
Gains and Losses are Fundamentally Different in Regret Minimization: The Sparse Case Vianney Perchet,Joon Kwon 2015 Pré-publication, Document de travail hal-01265075v1

Logiciel (1)

pyPLNmodels Bastien Batardière,Joon Kwon,Julien Chiquet 2024, ⟨swh:1:dir:e5d55f185fae7b64dd867a5ac05ae70cf9954dc5⟩ Logiciel hal-04738553v1