Analysis of the AutoML Challenge Series 2015–2018

no code implementations • Springer Cham 2019 • Isabelle Guyon, Lisheng Sun-Hosoya, Marc Boullé, Hugo Jair Escalante, Sergio Escalera, Zhengying Liu, Damir Jajetic, Bisakha Ray, Mehreen Saeed, Michèle Sebag, Alexander Statnikov, WeiWei Tu, Evelyne Viegas

The solutions of the winners are systematically benchmarked over all datasets of all rounds and compared with canonical machine learning algorithms available in scikit-learn.

AutoML BIG-bench Machine Learning +1

AutoML @ NeurIPS 2018 challenge: Design and Results

no code implementations • 12 Mar 2019 • Hugo Jair Escalante, Wei-Wei Tu, Isabelle Guyon, Daniel L. Silver, Evelyne Viegas, Yuqiang Chen, Wenyuan Dai, Qiang Yang

We organized a competition on Autonomous Lifelong Machine Learning with Drift that was part of the competition program of NeurIPS 2018.

AutoML BIG-bench Machine Learning

Explaining First Impressions: Modeling, Recognizing, and Explaining Apparent Personality from Videos

no code implementations • 2 Feb 2018 • Hugo Jair Escalante, Heysem Kaya, Albert Ali Salah, Sergio Escalera, Yagmur Gucluturk, Umut Guclu, Xavier Baro, Isabelle Guyon, Julio Jacques Junior, Meysam Madadi, Stephane Ayache, Evelyne Viegas, Furkan Gurpinar, Achmadnoer Sukma Wicaksana, Cynthia C. S. Liem, Marcel A. J. van Gerven, Rob van Lier

Explainability and interpretability are two critical aspects of decision support systems.