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DTSTART:20170312T100000
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DTSTART;TZID=America/Los_Angeles:20171012T160000
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DTSTAMP:20260419T052229
CREATED:20170728T083157Z
LAST-MODIFIED:20170728T083157Z
UID:577-1507824000-1507827600@rpm.physics.lbl.gov
SUMMARY:Barnabas Poczos (CMU) Title: Distribution Regression and its Applications
DESCRIPTION:Abstract: \nThe most common machine learning algorithms operate on\nfinite-dimensional vectorial feature representations. In\nmany applications\, however\, the natural representation of the data\nconsists of more complex objects\,\nfor example functions\, distributions\, and sets\, rather than\nfinite-dimensional vectors. In this talk\nwe will discuss machine learning algorithms that can operate directly\non these complex\nobjects. For this purpose\, we use nonparametric statistical methods\nthat can consistently estimate the inner product\, distance\, and\ncertain kernel functions between distributions\, sets\, and other\nobjects. We will discuss applications in various scientific areas\nincluding cosmology (e.g. estimating the mass of galaxy clusters\,\nfinding anomalous galaxy clusters\, estimating the cosmological\nparameters of our Universe\, accelerating cosmological simulations)\,\nfluid dynamics (finding anomalous events in turbulence data)\,\nneuroimaging\, and agriculture
URL:https://rpm.physics.lbl.gov/event/barnabas-poczos-cmu-tba/
LOCATION:HYBRID 50A-5132 (Sessler Conference Room)\, https://lbnl.zoom.us/j/91782268585\, 50A-5132
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