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UID:897@lincs.fr
DTSTART;TZID=Europe/Paris:20250507T140000
DTEND;TZID=Europe/Paris:20250507T150000
DTSTAMP:20250408T063502Z
URL:https://www.lincs.fr/events/resilient-and-efficient-decentralized-lear
 ning/
SUMMARY:Resilient and Efficient Decentralized Learning
DESCRIPTION:Decentralized learning enhances privacy\, scalability\, and
 fault tolerance by  distributing data and computation across nodes. A
 popular approach is Federated learning\, which relies on a central
 aggregator\, yet faces challenges such as server vulnerabilities\,
 scalability issues\, privacy risks and most importantly\, the single point
 of failure. Alternatively Gossip Learning offers fully decentralization
 through peer-to-peer exchanges of model updates\, ensuring robustness and
 privacy\, at the price of slower model convergence. In our work\, we
 introduce a novel decentralized learning framework called HEAL. By
 exploiting an innovative topology based on dynamic hubs\, HEAL delivers
 performance similar to that of Federated learning\, but with the
 decentralization and resilience of Gossip learning.
CATEGORIES:Seminars
LOCATION:Amphi 6\, 19 Place Marguerite Perey\, Palaiseau\, France
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=19 Place Marguerite Perey\,
 Palaiseau\, France;X-APPLE-RADIUS=100;X-TITLE=Amphi 6:geo:0,0
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TZID:Europe/Paris
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DTSTART:20250330T030000
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