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TZID:Europe/Paris
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BEGIN:VEVENT
UID:221@isdm.umontpellier.fr
DTSTART;TZID=Europe/Paris:20240516T140000
DTEND;TZID=Europe/Paris:20240516T140000
DTSTAMP:20260825T133159Z
URL:https://isdm.umontpellier.fr/events/no-bluffing-proving-ml-model-trust
 worthiness/
SUMMARY:No Bluffing: Proving ML Model Trustworthiness
DESCRIPTION:Room 02.124\, Building 5\, St Priest campus\n\nMachine Learning
  in Montpellier\, Theory &amp\; Practice\n\nOver the past few years\, we h
 ave seen significant efforts in building trustworthy ML. Many institutions
  are making privacy and fairness promises about their services. I start th
 e presentation by arguing that institutions might not adhere to their clai
 ms of using trustworthy ML across various services intentionally or accide
 ntally due to their interests in maximizing utility and minimizing costs/e
 fforts\, resulting in FairWashing /[NeurIPS2022]/ and PrivacyWashing. To a
 ddress these risks\, then\, I present Confidential-PROFITT /[Oral ICLR2023
 ] /and Confidential-DPproof /[Spotlight ICLR2024]/ frameworks that enable 
 institutions to directly prove to any interested party through the executi
 on of Zero Knowledge Proof protocols that they train ML models in a fair a
 nd privacy-preserving manner\, respectively\, while protecting the confide
 ntiality of their data and model. [NeurIPS2022] Washing The Unwashable : O
 n The (Im)possibility of Fairwashing Detection\, https://openreview.net/pd
 f?id=3vmKQUctNy [Oral ICLR2023] Confidential-PROFITT: Confidential PROof o
 f FaIr Training of Trees\, https://openreview.net/pdf?id=iIfDQVyuFD [Spotl
 ight ICLR2024] Confidential-DPproof: Confidential Proof of Differentially 
 Private Training\, https://openreview.net/pdf?id=PQY2v6VtGe\n\nMachine Lea
 rning in Montpellier\, Theory &amp\; Practice
ATTACH;FMTTYPE=image/jpeg:https://isdm.umontpellier.fr/wp-content/uploads/
 2026/06/ml-mtp-gC78d5.png
CATEGORIES:ML MTP
LOCATION:Saint Priest Campus - Building 5 - Room 02.124\, 860 rue St Priest
 \, Montpellier\, 
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=860 rue St Priest\, Montpel
 lier\, ;X-APPLE-RADIUS=100;X-TITLE=Saint Priest Campus - Building 5 - Room
  02.124:geo:0,0
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