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DTSTART:20230101T000000
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DTSTART;TZID=Asia/Seoul:20240528T163000
DTEND;TZID=Asia/Seoul:20240528T173000
DTSTAMP:20260418T010555
CREATED:20240418T043152Z
LAST-MODIFIED:20240705T153011Z
UID:8542-1716913800-1716917400@dimag.ibs.re.kr
SUMMARY:Yongho Shin (신용호)\, Three-way online correlated selection
DESCRIPTION:Two-way online correlated selection (two-way OCS) is an online algorithm that\, at each timestep\, takes a pair of elements from the ground set and irrevocably chooses one of the two elements\, while ensuring negative correlation in the algorithm’s choices. OCS was initially invented by Fahrbach\, Huang\, Tao\, and Zadimoghaddam (FOCS 2020\, JACM 2022) to break a natural long-standing barrier in edge-weighted online bipartite matching. They posed two open questions\, one of which was the following: Can we obtain n-way OCS for $n >2$\, in which the algorithm can be given $n >2$ elements to choose from at each timestep? \nIn this talk\, we affirmatively answer this open question by presenting a three-way OCS which is simple to describe: it internally runs two instances of two-way OCS\, one of which is fed with the output of the other. Contrast to its simple construction\, we face a new challenge in analysis that the final output probability distribution of our three-way OCS is highly elusive since it requires the actual output distribution of two-way OCS. We show how we tackle this challenge by approximating the output distribution of two-way OCS by a flatter distribution serving as a safe surrogate. \nThis is joint work with Hyung-Chan An.
URL:https://dimag.ibs.re.kr/event/2024-05-28/
LOCATION:Room B332\, IBS (기초과학연구원)
CATEGORIES:Discrete Math Seminar
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