Data science & artificial intelligence
For digitalized industry & services
Since its inception in 1985, AISTATS has been an interdisciplinary gathering of researchers at the intersection of artificial intelligence, machine learning, statistics and related areas.
The academic team of the Data Science and Artificial Intelligence for Digitalized Industry and Services chair presented four papers at the 2021 edition, which was held online last April:
Nonlinear Functional Output Regression: A Dictionary Approach
Dimitri Bouche, Marianne Clausel, François Roueff, Florence d’Alché-Buc
Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:235-243
When OT meets MoM: Robust estimation of Wasserstein Distance
Guillaume Staerman, Pierre Laforgue, Pavlo Mozharovskyi, Florence d’Alché-Buc
Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:136-144
Nearest Neighbour Based Estimates of Gradients: Sharp Nonasymptotic Bounds and Applications
Guillaume Ausset, Stephan Clémençon, François Portier
Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:532-540
Learning Fair Scoring Functions: Bipartite Ranking under ROC-based Fairness Constraints
Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:784-792
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