no code implementations • 26 Jan 2024 • Michael Wojnowicz, Preetish Rath, Eric Miller, Jeffrey Miller, Clifford Hancock, Meghan O'Donovan, Seth Elkin-Frankston, Thaddeus Brunye, Michael C. Hughes
Our hierarchical switching recurrent dynamical models can be learned via closed-form variational coordinate ascent updates to all latent chains that scale linearly in the number of individual time series.
no code implementations • 3 Jan 2019 • Michael Wojnowicz, Di Zhang, Glenn Chisholm, Xuan Zhao, Matt Wolff
However, the recent development of randomized principal component analysis (RPCA) has opened up the possibility of obtaining approximate principal components on very large datasets.
1 code implementation • 21 Sep 2017 • Michael Wojnowicz, Dinh Nguyen, Li Li, Xuan Zhao
Stochastic principal component analysis (SPCA) has become a popular dimensionality reduction strategy for large, high-dimensional datasets.