Adrien Pavão

According to our database, Adrien Pavão authored at least 15 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

AI Competitions and Benchmarks, Practical issues: Proposals, grant money, sponsors, prizes, dissemination, publicity.

Magali Richard, Yuna Blum, Justin Guinney, Gustavo Stolovitzky, Adrien Pavão

CoRR, 2024

2023

Methodology for Design and Analysis of Machine Learning Competitions. (Méthodologie pour la conception et l'analyse de compétitions en apprentissage automatique).

Adrien Pavão

PhD thesis, 2023

CodaLab Competitions: An Open Source Platform to Organize Scientific Challenges.

Adrien Pavao, Isabelle Guyon, Anne-Catherine Letournel, Dinh-Tuan Tran, Xavier Baró, Hugo Jair Escalante, Sergio Escalera, Tyler Thomas, Zhen Xu

J. Mach. Learn. Res., 2023

2022

Codabench: Flexible, easy-to-use, and reproducible meta-benchmark platform.

Zhen Xu, Sergio Escalera, Adrien Pavão, Magali Richard, Wei-Wei Tu, Quanming Yao, Huan Zhao, Isabelle Guyon

Patterns, 2022

Reinforcement learning for Energies of the future and carbon neutrality: a Challenge Design.

Gaëtan Serré, Eva Boguslawski, Benjamin Donnot, Adrien Pavão, Isabelle Guyon, Antoine Marot

CoRR, 2022

Filtering participants improves generalization in competitions and benchmarks.

Adrien Pavão, Isabelle Guyon, Zhengying Liu

Proceedings of the 30th European Symposium on Artificial Neural Networks, 2022

2021

Winning Solutions and Post-Challenge Analyses of the ChaLearn AutoDL Challenge 2019.

Zhengying Liu, Adrien Pavao, Zhen Xu, Sergio Escalera, Fabio Ferreira, Isabelle Guyon, Sirui Hong, Frank Hutter, Rongrong Ji, Júlio C. S. Jacques Júnior, Ge Li, Marius Lindauer, Zhipeng Luo, Meysam Madadi, Thomas Nierhoff, Kangning Niu, Chunguang Pan, Danny Stoll, Sébastien Treguer, Jin Wang, Peng Wang, Chenglin Wu, Youcheng Xiong, Arber Zela, Yang Zhang

IEEE Trans. Pattern Anal. Mach. Intell., 2021

Aircraft Numerical "Twin": A Time Series Regression Competition.

Adrien Pavao, Isabelle Guyon, Nachar Stéphane, Fabrice Lebeau, Martin Ghienne, Ludovic Platon, Tristan Barbagelata, Pierre Escamilla, Sana Mzali, Meng Liao, Sylvain Lassonde, Antonin Braun, Slim Ben-Amor, Liliana Cucu-Grosjean, Marwan Wehaiba, Avner Bar-Hen, Adriana Gogonel, Alaeddine Ben Cheikh, Marc Duda, Julien Laugel, Mathieu Marauri, Mhamed Souissi, Théo Lecerf, Mehdi Elion, Sonia Tabti, Julien Budynek, Pauline Le Bouteiller, Antonin Penon, Raphaël-David Lasseri, Julien Ripoche, Thomas E. Epalle

Proceedings of the 20th IEEE International Conference on Machine Learning and Applications, 2021

Judging competitions and benchmarks: a candidate election approach.

Adrien Pavao, Isabelle Guyon, Michael Vaccaro

Proceedings of the 29th European Symposium on Artificial Neural Networks, 2021

2020

Towards automated computer vision: analysis of the AutoCV challenges 2019.

Zhengying Liu, Zhen Xu, Sergio Escalera, Isabelle Guyon, Júlio C. S. Jacques Júnior, Meysam Madadi, Adrien Pavao, Sébastien Treguer, Wei-Wei Tu

Pattern Recognit. Lett., 2020

Generation and evaluation of privacy preserving synthetic health data.

Andrew Yale, Saloni Dash, Ritik Dutta, Isabelle Guyon, Adrien Pavao, Kristin P. Bennett

Neurocomputing, 2020

2019

Synthetic Event Time Series Health Data Generation.

Saloni Dash, Ritik Dutta, Isabelle Guyon, Adrien Pavao, Andrew Yale, Kristin P. Bennett

CoRR, 2019

Towards Automated Deep Learning: Analysis of the AutoDL challenge series 2019.

Zhengying Liu, Zhen Xu, Shangeth Rajaa, Meysam Madadi, Júlio C. S. Jacques Júnior, Sergio Escalera, Adrien Pavao, Sébastien Treguer, Wei-Wei Tu, Isabelle Guyon

Proceedings of the NeurIPS 2019 Competition and Demonstration Track, 2019

Privacy Preserving Synthetic Health Data.

Andrew Yale, Saloni Dash, Ritik Dutta, Isabelle Guyon, Adrien Pavao, Kristin P. Bennett

Proceedings of the 27th European Symposium on Artificial Neural Networks, 2019

Assessing privacy and quality of synthetic health data.

Andrew Yale, Saloni Dash, Ritik Dutta, Isabelle Guyon, Adrien Pavao, Kristin P. Bennett

Proceedings of the Conference on Artificial Intelligence for Data Discovery and Reuse, 2019