| Bayesian Optimization is Superior to Random Search for Machine Learning Hyperparameter Tuning: Analysis of the Black-Box Optimization Challenge 2020 R Turner, D Eriksson, M McCourt, J Kiili, E Laaksonen, Z Xu, I Guyon NeurIPS 2020 Comp & Demo Track, 2021 | 288 | 2021 |
| CodaLab Competitions: An open source platform to organize scientific challenges A Pavao, I Guyon, AC Letournel, X Baró, H Escalante, S Escalera, ... JMLR 2023, 2023 | 109 | 2023 |
| Winning solutions and post-challenge analyses of the ChaLearn AutoDL challenge 2019 Z Liu, A Pavao, Z Xu, S Escalera, F Ferreira, I Guyon, S Hong, F Hutter, ... TPAMI 2021, 2021 | 30 | 2021 |
| Didn’t see that coming: a survey on non-verbal social human behavior forecasting G Barquero, J Núnez, S Escalera, Z Xu, WW Tu, I Guyon, C Palmero PMLR 2022, 2022 | 24 | 2022 |
| Towards Automated Deep Learning: Analysis of the AutoDL challenge series 2019 Z Liu, Z Xu, S Rajaa, M Madadi, JCSJ Junior, S Escalera, A Pavao, ... NeurIPS 2019 Comp & Demo Track, 2020 | 22 | 2020 |
| Autocv challenge design and baseline results Z Liu, I Guyon, J Junior, M Madadi, S Escalera, A Pavao, H Escalante, ... CAp 2019, 2019 | 16 | 2019 |
| Comparison of Spatio-Temporal Models for Human Motion and Pose Forecasting in Face-to-Face Interaction Scenarios Supplementary Material G Barquero, J Núnez, Z Xu, S Escalera, WW Tu, I Guyon, C Palmero PMLR 2022, 2022 | 13 | 2022 |
| AutoML Meets Time Series Regression: Design and Analysis of the AutoSeries Challenge Z Xu, WW Tu, I Guyon ECML PKDD 2021, 2021 | 13 | 2021 |
| Codabench: Flexible, easy-to-use, and reproducible meta-benchmark platform Z Xu, S Escalera, A Pavão, M Richard, WW Tu, Q Yao, H Zhao, I Guyon Cell Patterns 2022, 2022 | 10 | 2022 |
| Towards automated computer vision: analysis of the AutoCV challenges 2019 Z Liu, Z Xu, S Escalera, I Guyon, JCSJ Júnior, M Madadi, A Pavao, ... PRL 2020, 2020 | 9 | 2020 |
| Overview and unifying conceptualization of automated machine learning Z Liu, Z Xu, M Madadi, J Jacques Junior, S Escalera, S Rajaa, I Guyon ECML PKDD 2019 Workshop, 2019 | 8 | 2019 |
| How far are we from true AutoML: reflection from winning solutions and results of AutoDL challenge Z Liu, A Pavao, Z Xu, S Escalera, I Guyon, JCSJ Junior, M Madadi, ... ICML 2020 Workshop, 2020 | 3 | 2020 |
| AI Competitions and Benchmarks: How to ensure a long-lasting impact of a challenge with post-challenge paper, benchmarks and other dissemination action A Marot, D Rousseau, Z Xu arXiv preprint arXiv:2312.06036, 2023 | | 2023 |
| Understanding and Simplifying Architecture Search in Spatio-Temporal Graph Neural Networks Z Xu, Q Yao, Y Li, Q Yang TMLR 2023, 2023 | | 2023 |
| Bridging the Gap of AutoGraph between Academia and Industry: Analysing AutoGraph Challenge at KDD Cup 2020 Z Xu, L Wei, H Zhao, R Ying, Q Yao, WW Tu, I Guyon Frontiers in Artificial Intelligence 2022, 2022 | | 2022 |
Isabelle GuyonDirector of Research, Google; Prof. UPSaclay; President ChaLearnVerified email at chalearn.org
