Preprint submitted to NeurIPS2018 Volume of Springer Series on Challenges in Machine LearningInternational audienceWe organized a competition on Autonomous Lifelong Machine Learning with Drift that was part of the competition program of NeurIPS 2018. This data driven competition asked participants to develop computer programs capable of solving supervised learning problems where the i.i.d. assumption did not hold. Large data sets were arranged in a lifelong learning and evaluation scenario and CodaLab was used as the challenge platform. The challenge attracted more than 300 participants in its two month duration. This chapter describes the design of the challenge and summarizes its main results
International audienceFollowing the success of the first AutoML challenges , we designed a new chall...
International audienceThe success of machine learning in many domains crucially relies on human mach...
CodaLab Competitions is an open source web platform designed to help data scientists and research te...
Preprint submitted to NeurIPS2018 Volume of Springer Series on Challenges in Machine LearningInterna...
International audienceThe ChaLearn AutoML Challenge 1 (NIPS 2015-ICML 2016) consisted of six rounds ...
ChaLearn is organizing the Automatic Machine Learning (AutoML) contest for IJCNN 2015, which challen...
National audienceWe give a brief account of the main findings of our post-hoc analysis of the first ...
International audienceThis paper reports the results and post-challenge analyses of ChaLearn’s AutoD...
International audienceWe present the design and results of recent competitions in Automated Deep Lea...
International audienceFollowing the success of the first AutoML challenges , we designed a new chall...
International audienceThe success of machine learning in many domains crucially relies on human mach...
CodaLab Competitions is an open source web platform designed to help data scientists and research te...
Preprint submitted to NeurIPS2018 Volume of Springer Series on Challenges in Machine LearningInterna...
International audienceThe ChaLearn AutoML Challenge 1 (NIPS 2015-ICML 2016) consisted of six rounds ...
ChaLearn is organizing the Automatic Machine Learning (AutoML) contest for IJCNN 2015, which challen...
National audienceWe give a brief account of the main findings of our post-hoc analysis of the first ...
International audienceThis paper reports the results and post-challenge analyses of ChaLearn’s AutoD...
International audienceWe present the design and results of recent competitions in Automated Deep Lea...
International audienceFollowing the success of the first AutoML challenges , we designed a new chall...
International audienceThe success of machine learning in many domains crucially relies on human mach...
CodaLab Competitions is an open source web platform designed to help data scientists and research te...