15 citations · 45 across the 31 of their papers we have counts for
5 papers · 1 filter
t-SNE, Forceful Colorings and Mean Field Limits
Yulan Zhang, Stefan Steinerberger
t-SNE is one of the most commonly used force-based nonlinear dimensionality reduction methods. This paper has two contributions: the first is forceful colorings, an idea that is al…
Neural Collapse with Cross-Entropy Loss
Jianfeng Lu, Stefan Steinerberger
We consider the variational problem of cross-entropy loss with feature vectors on a unit hypersphere in . We prove that when , the global minimum is…
The Spectral Underpinning of word2vec
Ariel Jaffe, Yuval Kluger, Ofir Lindenbaum +3
word2vec due to Mikolov \textit{et al.} (2013) is a word embedding method that is widely used in natural language processing. Despite its great success and frequent use, theoretica…
Heavy-tailed kernels reveal a finer cluster structure in t-SNE visualisations
Dmitry Kobak, George Linderman, Stefan Steinerberger +2
T-distributed stochastic neighbour embedding (t-SNE) is a widely used data visualisation technique. It differs from its predecessor SNE by the low-dimensional similarity kernel: th…
Clustering with t-SNE, provably
George C. Linderman, Stefan Steinerberger
t-distributed Stochastic Neighborhood Embedding (t-SNE), a clustering and visualization method proposed by van der Maaten & Hinton in 2008, has rapidly become a standard tool in a…