"FairGBM: Gradient Boosting with Fairness Constraints", André Cruz (Max Planck Institute for Intelligent Systems)

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Diogo Pernes

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Mar 14, 2023, 8:15:39 AM3/14/23
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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 Labs
http://labs.priberam.com/

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If you are interested in working with us please consult the available positions at priberam.com/careers.

Image result for priberam logoPRIBERAM SEMINARS

__________________________________________________

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.


Diogo Pernes

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Mar 21, 2023, 8:05:31 AM3/21/23
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Just a friendly reminder that our session is starting in one hour! :)


From: priberam_...@googlegroups.com <priberam_...@googlegroups.com> on behalf of Diogo Pernes <diogo....@priberam.pt>
Sent: Tuesday, March 14, 2023 12:15 PM
To: priberam_...@googlegroups.com; isr-...@isr.tecnico.ulisboa.pt; si...@omni.isr.ist.utl.pt
Subject: [Priberam ML Seminars] "FairGBM: Gradient Boosting with Fairness Constraints", André Cruz (Max Planck Institute for Intelligent Systems)
 
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