[dave_sullivan]

We're rolling our own for release, but right now we're borrowing liberally from the Barnes-Hut-SNE implementation here: http://homepage.tudelft.nl/19j49/t-SNE.html Barnes-Hut is a modification that makes T-SNE a lot more efficient, so I could train on hundreds of thousands of vectors instead of <10,000.

However, I'm wondering if there's something I'm missing that makes it not suitable for 3d--IE, maybe the assumptions being made to speed things up break down after the 2nd dimension. Also, there's interesting discussion in the literature about whether or not T-SNE is a good dimensionality reduction technique in general (as opposed to only a very powerful visualization technique), so my next step is probably going to be running the vectors through an autoencoder to generate 3d coordinates and then plotting those and comparing the visualizations.

Re: another example of TSNE w/ text--yeah, I've only seen this http://homepage.tudelft.nl/19j49/t-SNE_files/semantic_tsne.j... which seems to work but isn't interactive. Frankly, I'm surprised we got it to work with three.js--we're able to render as many as 250,000 unique words and it runs smooth (it just takes longer to download--this demo has 25,000).

[a1k0n]

Barnes-Hut uses a quadtree, doesn't it? I don't know whether the code was adapted to use an octree in 3D instead; maybe it was? FWIW there's a really interesting Google techtalk on how it works: http://www.youtube.com/watch?v=RJVL80Gg3lA