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DTSTART:20261101T010000
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DESCRIPTION:Join us for an in-depth session on SGCL (Supervised Graph Contrastive Learning)\, exploring how self-supervised contrastive learning and supervised learning can be efficiently unified for graph learning for scalable recommendation and ranking. We’ll dive into the core techniques and applications of SGCL\, related work\, and open the floor for Q&A with the paper’s first author. Perfect for both newcomers and experienced researchers interested in modern graph learning and IR!\n\n------\n\nCreate your own Add to Calendar links with addevent.com/r/a \n
X-ALT-DESC;FMTTYPE=text/html:Join us for an in-depth session on SGCL (Supervised Graph Contrastive Learning), exploring how self-supervised contrastive learning and supervised learning can be efficiently unified for graph learning for scalable recommendation and ranking. We’ll dive into the core techniques and applications of SGCL, related work, and open the floor for Q&A with the paper’s first author. Perfect for both newcomers and experienced researchers interested in modern graph learning and IR!
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Create your own Add to Calendar links with addevent.com/r/a
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SUMMARY:Weizhi Zhang - Towards More Efficient and Scalable Graph Recommendation (Ret&Search)
DTSTART;TZID=America/Toronto:20250806T100000
DTEND;TZID=America/Toronto:20250806T110000
DTSTAMP:20260906T203222Z
TRANSP:OPAQUE
STATUS:CONFIRMED
SEQUENCE:0
LOCATION:https://meet.google.com/jpk-xpty-rmg?hs=122&authuser=0
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