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Activity Number: 456 - Introductory Lectures on Recent Advancements in Computational Statistics
Type: Invited
Date/Time: Wednesday, August 1, 2018 : 8:30 AM to 10:20 AM
Sponsor: Statistics Surveys Online Journal
Abstract #326503
Title: Visualizing Data Using T-SNE
Author(s): Laurens van der Maaten*
Companies: Facebook AI Research
Keywords: Dimensionality reduction; t-SNE; Embedding; Data visualization

Visualization techniques are essential tools for every data scientist. Unfortunately, the majority of visualization techniques can only be used to inspect a limited number of variables of interest simultaneously. An effective way to visualize high-dimensional data is to represent each data object by a two-dimensional point in such a way that similar objects are represented by nearby points, and that dissimilar objects are represented by distant points. The resulting two-dimensional points can be visualized in a scatter plot. This leads to a map of the data that reveals the underlying structure of the objects, such as the presence of clusters. The talk presents techniques to embed high-dimensional objects in a two-dimensional map. In particular, it focuses on a technique called t-Distributed Stochastic Neighbor Embedding (t-SNE) that produces substantially better results than alternative techniques. We demonstrate the value of t-SNE in domains such as computer vision and bioinformatics. In addition, we show how to scale up t-SNE to sets with millions of objects.

Authors who are presenting talks have a * after their name.

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