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DTSTART:19700308T020000
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BEGIN:VEVENT
DTSTAMP:20260417T190158Z
LOCATION:West Building\, Rooms 118-120
DTSTART;TZID=America/Los_Angeles:20250813T141000
DTEND;TZID=America/Los_Angeles:20250813T142000
UID:siggraph_SIGGRAPH 2025_sess155_papers_867@linklings.com
SUMMARY:Accelerated Gamut Discovery via Massive Parallelization
DESCRIPTION:Navid Ansari, Hans-Peter Seidel, and Vahid Babaei (Max Planck 
 Institute for Informatics)\n\nThis paper proposes a scalable framework usi
 ng Bayesian Neural Networks and a novel 2mD acquisition function to effici
 ently discover gamut boundaries in performance space. Combining NSGA-II's 
 diversity and Bayesian Optimization's efficiency, the method enables large
 -batch, parallel optimization, outperforming traditional approaches in rea
 l-world engineering and fabrication tasks.\n\nInterest Area: Research & Ed
 ucation\n\nRecording: Livestreamed, Not Livestreamed, Recorded, Not Record
 ed\n\nRegistration Category: Full Conference, Virtual Access, Wednesday\n\
 nSession Chair: Timothy Langlois (Adobe)\n\n
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