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Causality and big data analytics: risk, challenges and perspectives

June 2020

Conference: 2020 French-German Summer School with Industry on ML, AI

Project: Causal discovery from observation data

Authors:

Gianluca Bontempi

Université Libre de Bruxelles

Presentation on causality issues in big data analytics

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Project

Scalable machine learning for big data analytics

The advent of big data analytics demands the adoption of effective and accurate machine learning methods. However most of these techniques have been designed and assessed in an epoch when all data could reside in memory and be rapidly accessible.This research project aims to study the impact on the machine learning procedure of the large availability of massive datasets. Notably the focus is on the impact of big data on model selection, bias/variance tradeoff and parallel implementations. ... [more]

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Project

Causal discovery from observation data

Gianluca Bontempi

The relationship between statistical dependency and causality lies at the heart of all statistical approaches to causal inference. Recent results have shown that causal directionality can be infer red with good accuracy also in Markov indistinguishable configurations thanks to data driven approaches. I am working on a supervised machine learning approach to infer the existence of a directed causal link between two variables in multivariate settings with n > 2 variables. The approach relies on the asymmetry of some conditional (in)dependence relations between the mem- bers of the Markov blankets of two variables causally connected. ... [more]

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Project

TCGAbiolinks

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Project

Multi-variate and multi-step-ahead time series forecasting

This is probably the hardest prediction task in the world. The goal is to design, assess and compare a number of techniques for this task.

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Data

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IEEE Big Data presentation slides

August 2016

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Presentation

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Discovery Science 2016 tutorial: "Perspectives of feature selection in bioinformatics: from relevanc...

October 2016

Gianluca Bontempi

Discovery Science 2016 tutorial: ”Perspectives of feature selection in bioinformatics: from relevance to causal inference”, Bari, 2016, October the 21st

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Presentation

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"From supervised learning to causal inference in large dimensional settings": PhD course

June 2020

Gianluca Bontempi

My class at the Summer school "Machine Learning for Non-Matrix Data", PhD Course, Politecnico di Milano . Other presentations and videos available at https://tinyurl.com/ybhmas44

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Presentation

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