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math.ST2020★ 1 cited
Scalability and robustness of spectral embedding: landmark diffusion is all you need
Chao Shen, Hau-Tieng Wu
While spectral embedding is a widely applied dimension reduction technique in various fields, so far it is still challenging to make it scalable to handle ``big data''. On the othe…
math.ST2018
Connecting Dots -- from Local Covariance to Empirical Intrinsic Geometry and Locally Linear Embedding
John Malik, Chao Shen, Hau-Tieng Wu +1
Local covariance structure under the manifold setup has been widely applied in the machine learning society. Based on the established theoretical results, we provide an extensive s…