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Learning Overcomplete Latent Variable Models through Tensor Power Method
Simons Institute for the Theory of Computing
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55:35
Tensor Decompositions for Estimating Latent Variable Models
Simons Institute for the Theory of Computing
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Tensor Methods for Learning Latent Variable Models: Theory and Practice
Simons Institute for the Theory of Computing
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55:49
Tensor Decompositions for Learning Latent Variable Models I
Simons Institute for the Theory of Computing
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Tensor Decompositions for Learning Latent Variable Models II
Simons Institute for the Theory of Computing
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1:08:06
Tensor Decompositions for Learning Hidden Variable Models
Microsoft Research
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1:10:54
Tensor Decompositions: Uniqueness and Smoothed Analysis
Simons Institute for the Theory of Computing
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48:53
Spectral Algorithms for Learning Latent Variable Models
Simons Institute for the Theory of Computing
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33:38
Furong Huang: "Understanding, Interpreting & Designing NN Models Through Tensor Representations"
Institute for Pure & Applied Mathematics (IPAM)
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1:03:23
Discovery of Latent Factors in High-dimensional Data via Tensor Decomposition
Microsoft Research
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51:33
Learning Mixture of Gaussians using Moment Tensor
Simons Institute for the Theory of Computing
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