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Title: Visual Analytics via Real-time Interactive 2D Embedding
The lecture covers basic and advanced techniques of real-time interactive 2D embedding of high-dimensional data. I will describe various 2D embedding methods ranging from multi-dimensional scaling to t-distributed stochastic neighbor embedding, as well as its visual analytic applications for real-time interactive 2D embedding.
Jaegul Choo ( https://sites.google.com/site/jaegulchoo/ ) is an assistant professor in the Dept. of Computer Science and Engineering at Korea University. He has been a research scientist at Georgia Tech from 2011 to 2015, where he also received M.S in 2009 and Ph.D in 2013. His research focuses on visual analytics for high-dimensional data, which leverages both data mining and interactive visualization. He has been publishing in premier venues in both fields such as TVCG, VAST, CG&A, KDD, WWW, WSDM, AAAI, IJCAI, ICDM, TKDD, DMKD, ICWSM, and SDM, . He earned earned the Best Student Paper Award at ICDM in 2016, the Outstanding Research Scientist Award at Georgia Tech in 2015 and the Best Poster Award at IEEE VAST (as part of IEEE VIS) in 2014, and he was nominated as one of the four finalists in IEEE Visualization Pioneers Group dissertation award in 2013.
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