Understanding Tensor Decompositions For Learning Hidden Variable Models
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Key Takeaways about Tensor Decompositions For Learning Hidden Variable Models
- Tensor
- Daniel Hsu, Columbia University https://simons.berkeley.edu/talks/daniel-hsu-01-27-2017-2 Foundations of Machine
- Tensors
- Moses Charikar, Princeton University Semidefinite Optimization, Approximation and Applications ...
- Incorporating latent or
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 Animashree Anandkumar, UC Irvine Spectral Algorithms: From Theory to Practice ...
Watch part 2/2 here: https://youtu.be/npPaMknLJWQ
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