Understanding Learning Overcomplete Latent Variable Models Through Tensor Power Method
Exploring Learning Overcomplete Latent Variable Models Through Tensor Power Method reveals several interesting facts. Rong Ge, Microsoft Research Semidefinite Optimization, Approximation and Applications ...
Key Takeaways about Learning Overcomplete Latent Variable Models Through Tensor Power Method
- Daniel Hsu, Columbia University https://simons.berkeley.edu/talks/daniel-hsu-01-27-2017-1 Foundations of Machine
- See https://uvaml1.github.io for annotated slides and a week-by-week overview of the course. This work is licensed under a ...
- Talk at Strata 2015 at the Hardcore Data Science Track.
- Daniel Hsu, Columbia University https://simons.berkeley.edu/talks/daniel-hsu-01-27-2017-2 Foundations of Machine
- LATENT VARIABLE MODELS – THE HIDDEN STRUCTURE
Detailed Analysis of Learning Overcomplete Latent Variable Models Through Tensor Power Method
Animashree Anandkumar, UC Irvine Spectral Algorithms: From Theory to Practice ... Incorporating Sham Kakade, Microsoft Research New England
Sum-Of-Squares Algorithms For Over-Complete Tensor Decomposition
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