no code implementations • ICML 2020 • Ferdinando Cicalese, Francisco Sergio de Freitas Filho, Eduardo Laber, Marco Molinaro
We focus on the model of Machine Teaching with a black box learner introduced in [Dasgupta et al., ICML 2019], where the teaching is done interactively without having any knowledge of the Learner's algorithm and class of hypotheses, apart from the fact that it contains the target hypothesis $h^*$.
1 code implementation • 4 Feb 2022 • Sergio Filho, Eduardo Laber, Pedro Lazera, Marco Molinaro
Consider a scenario in which we have a huge labeled dataset ${\cal D}$ and a limited time to train some given learner using ${\cal D}$.
no code implementations • 22 Dec 2020 • Katharina A. Lutz, Mark Allen, Caroline Bot, Miriam Cortés-Contreras, Sébastien Derriere, Markus Demleitner, Hendrik Heinel, Fran Jiménez-Esteban, Marco Molinaro, Ada Nebot, Enrique Solano, Mark Taylor
In addition to the VO schools on the European level, different national teams have also put effort into VO dissemination.
Instrumentation and Methods for Astrophysics
no code implementations • ICML 2018 • Eduardo Laber, Marco Molinaro, Felipe Mello Pereira
In practice, decision-tree inducers use heuristics for finding splits with small impurity when they consider nominal attributes with a large number of distinct values.
