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Ciclo Seminarios Instituto Sistemas Complejos de Ingeniería (ISCI)

12:00 horas, Sala B05, Beauchef 851, Santiago

Invitado: Bernhard Schölkopf, Director at the Max Planck Institute for Intelligent Systems

Título de la conferencia: “AI, Machine learning, and causality”

Abstract
Modern AI builds on machine learning, using data to automatically find dependences in the world, with the goal of predicting future observations. Most machine learning methods build on statistics, but one can also try to go beyond this, assaying causal structures underlying statistical dependences. Causal knowledge allows richer representations of information, and forms of reasoning that are beyond standard statistical machine learning models. Can it also help prediction in machine learning tasks? We argue that this is indeed the case, due to the fact that causal models are more robust to changes that occur in real world datasets. We discuss implications of causality for machine learning tasks, and argue that many of the hard issues benefit from the causal
viewpoint. This includes domain adaptation, semi-supervised learning, transfer, life-long learning, as well as an application to the removal of systematic errors in astronomical problems.

Consultas a seminarios@isci.cl

Almuerzos disponibles previa inscripción AQUÍ

Organiza: Instituto Sistemas Complejos de Ingeniería (ISCI)