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0 pointsjszymborski2y ago0 comments

It's[0] a non-linear dimensionality reduction technique in the vein of t-SNE[1] that is very well known in the field.

My two cents is that if your problem can be solved with something like UMAP + kNN[2], then you really shouldn't be using Deep Learning to solve it.

0 comments

Doesn’t your choice of initialization really affect the results? Lior Pachter really seems to keep beating that drum

There's some work[0] that argues that UMAP's performance relative to t-SNE is not that great when you control for the initialization.

I'm not sure where I sit on that, but regardless, my understanding is that getting UMAP to separate MNIST doesnt really require you to turn knobs.

j / k navigate · click thread line to collapse

0 pointsjszymborski2y ago0 comments

It's[0] a non-linear dimensionality reduction technique in the vein of t-SNE[1] that is very well known in the field.

My two cents is that if your problem can be solved with something like UMAP + kNN[2], then you really shouldn't be using Deep Learning to solve it.

Doesn’t your choice of initialization really affect the results? Lior Pachter really seems to keep beating that drum

There's some work[0] that argues that UMAP's performance relative to t-SNE is not that great when you control for the initialization.

I'm not sure where I sit on that, but regardless, my understanding is that getting UMAP to separate MNIST doesnt really require you to turn knobs.

j / k navigate · click thread line to collapse