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UID:624@lincs.fr
DTSTART;TZID=Europe/Paris:20210407T110000
DTEND;TZID=Europe/Paris:20210407T120000
DTSTAMP:20210414T054518Z
URL:https://www.lincs.fr/events/design-of-algorithms-for-the-production-of
 -training-data/
SUMMARY:Design of algorithms for the production of training data
DESCRIPTION:There is a well-known saying in the supervised machine learning
 community: "garbage in\, garbage out". The performance of a supervised
 learning algorithm depends critically on the quantity and quality of
 training data. This training data is obtained from raw data through data
 labeling performed by human experts. The growing use of machine learning
 tools makes the design of efficient data labeling algorithms more relevant
 than ever.\n\nWe will present progress made in collaboration with Maya
 Stein (University of Chile) and Alexander Scott (Oxford University) on a
 problem proposed by Maria Laura Maag (Nokia). It corresponds to the
 reconstruction of a set partition using as few queries as possible\, each
 query asking whether two elements belong to the same block. We characterize
 the optimal algorithms and analyze the optimal distribution of the number
 of queries.\n\nSlides (Quentin)\n\nSlides (Élie)
CATEGORIES:Network Theory,Working Group,Youtube
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TZID:Europe/Paris
X-LIC-LOCATION:Europe/Paris
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DTSTART:20210328T030000
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