Dear all,
We are pleased to announce that we will be holding the second session of this year's
Priberam Machine Learning Seminars next Tuesday, March 21. Our featured speaker will be
André Cruz, a PhD candidate at the Max Planck Institute for Intelligent Systems and formerly a member of the FATE AI research group at
Feedzai. He will be presenting his research on Gradient Boosting Machines with fairness constraints (FairGBM), which has been accepted at ICLR 2023.
The event will occur at 1 PM in Instituto Superior Técnico (room PA2), and we will provide lunch bags for attendees. To learn more about the event and register (which is mandatory if you plan to attend), please follow the link below:
We look forward to seeing you all there!
Kind regards,
Diogo Pernes
Priberam is hiring!
If you are interested in working with us please consult the available positions at priberam.com/careers.
PRIBERAM SEMINARS
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Priberam Machine Learning Lunch Seminar
Speaker: André
Cruz (Max Planck Institute for Intelligent Systems)
Venue: Instituto Superior Técnico (room PA2)
Date: Tuesday,
March 21, 2023
Time: 1
PM
Title:
FairGBM: Gradient Boosting with Fairness Constraints
Abstract:
Tabular data is prevalent in many high-stakes domains, from financial services to public policy. In these
settings, Gradient Boosted Machines (GBM) are still the state-of-the-art. However, existing in-training fairness interventions are either incompatible with GBMs, or incur significant performance losses while taking considerably longer to train.We present FairGBM,
a framework for training GBMs under fairness constraints, with little to no impact on predictive performance. We validate our method on five large-scale public datasets, as well as a real-world case-study of account opening fraud. Our open-source implementation
shows an order of magnitude speedup in training time when compared with related work. https://github.com/feedzai/fairgbm
Short Bio:
André Cruz holds a Computer Science MSc from FEUP and is currently a PhD student at the Max Planck Institute
for Intelligent Systems, in Germany. André's current research focus is on Human-ML collaboration and the feedback loops between deployed ML systems and society at large. In the two years prior André worked at Feedzai as part of the FATE AI research group -
Fairness, Accountability, Transparency, and Ethics in AI.