Alexandre Quemy

[ IBM ]

Check the video recording from the live stream –> HERE

PhD student in Artificial Intelligence & Senior Engineer at IBM

My doctoral thesis is entitled “End-to-end approach to classification in unstructured spaces with application to judicial decisions” and focused both on theoretical and practical Machine Learning. I try to reduce the need for expertise required in the usual Machine Learning workflow as it is the first obstacle to the adoption of artificial intelligence solutions.

My main contributions are:
– A new mathematical theory for classification, with “good” properties (explainability, no metric required, no hyperparameter,…) based on hypergraphs and metric learning,
– A generic method to automate most of data preparation using standard hyperparameter tuning techniques,
– The largest curated datasets about the legal domain, on which I reached over 94% accuracy predicting the outcome of a judgment.

[ Releated Sessions ]

All Sessions by Alexandre Quemy

Day 2
A better approach to data science: the example of COVID-19 14:00