Understanding Tensor Decompositions For Learning Hidden Variable Models
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Key Takeaways about Tensor Decompositions For Learning Hidden Variable Models
- Tensor decompositions
- Animashree Anandkumar, UC Irvine Spectral Algorithms: From Theory to Practice ...
- Talk starts at 2:20 Dr. Tamara Kolda from Sandia National Labs speaking in the Data-driven methods for science and engineering ...
- Incorporating latent or
- Luke Oeding, Auburn University Algebraic Geometry Boot Camp http://simons.berkeley.edu/talks/luke-oeding-2014-09-03.
Detailed Analysis of Tensor Decompositions For Learning Hidden Variable Models
Daniel Hsu, Columbia University https://simons.berkeley.edu/talks/daniel-hsu-01-27-2017-1 Foundations of Machine Sham Kakade, Microsoft Research New England Daniel Hsu, Columbia University https://simons.berkeley.edu/talks/daniel-hsu-01-27-2017-2 Foundations of Machine
Rong Ge, Microsoft Research Semidefinite Optimization, Approximation and Applications ...
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