Tensor Decompositions For Learning Latent Variable Models I

May 25, 2026
Quick Summary: Rong Ge, Microsoft Research Semidefinite Optimization, Approximation and Applications ... Animashree Anandkumar, UC Irvine Spectral Algorithms: From Theory to Practice ...

Tensor Decompositions For Learning Latent Variable Models I -

Rong Ge, Microsoft Research Semidefinite Optimization, Approximation and Applications ... Animashree Anandkumar, UC Irvine Spectral Algorithms: From Theory to Practice ... This is a 3-minute spotlight video for the NIPS 2016 conference paper.

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  • Rong Ge, Microsoft Research Semidefinite Optimization, Approximation and Applications ...
  • Animashree Anandkumar, UC Irvine Spectral Algorithms: From Theory to Practice ...
  • This is a 3-minute spotlight video for the NIPS 2016 conference paper.

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Tensor Decompositions for Learning Latent Variable Models I

Tensor Decompositions for Learning Latent Variable Models I

Read more details and related context about Tensor Decompositions for Learning Latent Variable Models I.

Tensor Methods for Learning Latent Variable Models: Theory and Practice

Tensor Methods for Learning Latent Variable Models: Theory and Practice

Animashree Anandkumar, UC Irvine Spectral Algorithms: From Theory to Practice ...

Tensor Decompositions for Estimating Latent Variable Models

Tensor Decompositions for Estimating Latent Variable Models

Read more details and related context about Tensor Decompositions for Estimating Latent Variable Models.

Archive: Learning Latent Variable Models: Overlapping Community and Overcomplete Models

Archive: Learning Latent Variable Models: Overlapping Community and Overcomplete Models

Read more details and related context about Archive: Learning Latent Variable Models: Overlapping Community and Overcomplete Models.

Tensor Decompositions for Learning Hidden Variable Models

Tensor Decompositions for Learning Hidden Variable Models

Read more details and related context about Tensor Decompositions for Learning Hidden Variable Models.

Tensor Decompositions for Learning Latent Variable Models II

Tensor Decompositions for Learning Latent Variable Models II

Read more details and related context about Tensor Decompositions for Learning Latent Variable Models II.

AAAI'21 STELAR: Spatio-temporal Tensor Factorization with Latent Epidemiological Regularization

AAAI'21 STELAR: Spatio-temporal Tensor Factorization with Latent Epidemiological Regularization

Read more details and related context about AAAI'21 STELAR: Spatio-temporal Tensor Factorization with Latent Epidemiological Regularization.

CS 182: Lecture 18: Part 1: Latent Variable Models

CS 182: Lecture 18: Part 1: Latent Variable Models

Read more details and related context about CS 182: Lecture 18: Part 1: Latent Variable Models.

Blind Regression: Nonparametric Regression for Latent Variable Models

Blind Regression: Nonparametric Regression for Latent Variable Models

This is a 3-minute spotlight video for the NIPS 2016 conference paper. (Link:

Learning Overcomplete Latent Variable Models through Tensor Power Method

Learning Overcomplete Latent Variable Models through Tensor Power Method

Rong Ge, Microsoft Research Semidefinite Optimization, Approximation and Applications ...