I&#x27;ve just skimmed the paper, and this new algorithm looks very nice -- the authors call it &quot;LargeVis.&quot;<p>According to the paper, LargeVis improves on Barnes-Hut t-SNE in two ways: first, it uses the idea that &quot;the neighbors of my neighbors are likely my neighbors too&quot; to construct an approximate graph of nearest neighbors in the high-dimensional space in a manner that is computationally much more efficiently than the method used by t-SNE.  Second, the authors apparently have found a clever way to use SGD to map this graph to two (or three) dimensions with computational cost <i>linear</i> in the number of nodes.<p>If the authors release an open-source implementation, LargeVis looks likely to supplant t-SNE as the go-to algorithm for visualizing high-dimensional data.