BEGIN:VCALENDAR VERSION:2.0 PRODID:researchseminars.org CALSCALE:GREGORIAN X-WR-CALNAME:researchseminars.org BEGIN:VEVENT SUMMARY:Nicholas Richardson (UBC) DTSTART:20260120T233000Z DTEND:20260121T003000Z DTSTAMP:20260513T201628Z UID:SFUOR/63 DESCRIPTION:Title: O ptimization and applications for unsupervised signal demixing\nby Nich olas Richardson (UBC) as part of PIMS-CORDS SFU Operations Research Semina r\n\nLecture held in ASB 10908.\n\nAbstract\nThroughout scientific and com mercial domains\, we are often interested in separating mixed signals into their component sources. Supervised deep learning is state-of-the-art whe n large and well-labeled datasets can be used. But in many applications\, large scale collection and labelling can be too impraticable\, expensive\, or behind copyright laws. This talk will explore a number of applications from sediment analysis\, genome sequencing\, and audio source separation that fall into the scarce data category. We will see a few approaches I ha ve used to model and solve these problems such as sparse feature models an d tensor factorizations. These unsupervised learning techniques avoid a tr aining phase and have the advantage of adapting to the specific example at hand.\n LOCATION:https://researchseminars.org/talk/SFUOR/63/ END:VEVENT END:VCALENDAR