Learning Overcomplete Latent Variable Models Through Tensor Power Method

May 26, 2026
Quick Context: Moses Charikar, Princeton University Semidefinite Optimization, Approximation and Applications ... Rong Ge, Microsoft Research Semidefinite Optimization, Approximation and Applications ...

Learning Overcomplete Latent Variable Models Through Tensor Power Method -

Moses Charikar, Princeton University Semidefinite Optimization, Approximation and Applications ... Rong Ge, Microsoft Research Semidefinite Optimization, Approximation and Applications ... Animashree Anandkumar, UC Irvine Spectral Algorithms: From Theory to Practice ...

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  • Moses Charikar, Princeton University Semidefinite Optimization, Approximation and Applications ...
  • Rong Ge, Microsoft Research Semidefinite Optimization, Approximation and Applications ...
  • Animashree Anandkumar, UC Irvine Spectral Algorithms: From Theory to Practice ...

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Learning Overcomplete Latent Variable Models through Tensor Power Method
Tensor Decompositions for Estimating Latent Variable Models
Archive: Learning Latent Variable Models: Overlapping Community and Overcomplete Models
Tensor Methods for Learning Latent Variable Models: Theory and Practice
Tensor Decompositions for Learning Latent Variable Models I
Tensor Decompositions for Learning Latent Variable Models II
Tensor Decompositions for Learning Hidden Variable Models
Aravindan Vijayaraghavan: "Smoothed Analysis for Tensor Decompositions and Unsupervised Learning"
Tensor Decompositions: Uniqueness and Smoothed Analysis
lec6 18409 - Tensor Methods (topic models)
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Tensor Decompositions for Estimating Latent Variable Models Archive: Learning Latent Variable Models: Overlapping Community and Overcomplete Models Tensor Methods for Learning Latent Variable Models: Theory and Practice Tensor Decompositions for Learning Latent Variable Models I Tensor Decompositions for Learning Latent Variable Models II Tensor Decompositions for Learning Hidden Variable Models Aravindan Vijayaraghavan: "Smoothed Analysis for Tensor Decompositions and Unsupervised Learning"
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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 ...

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 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 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 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.

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.

Aravindan Vijayaraghavan: "Smoothed Analysis for Tensor Decompositions and Unsupervised Learning"

Aravindan Vijayaraghavan: "Smoothed Analysis for Tensor Decompositions and Unsupervised Learning"

Read more details and related context about Aravindan Vijayaraghavan: "Smoothed Analysis for Tensor Decompositions and Unsupervised Learning".

Tensor Decompositions: Uniqueness and Smoothed Analysis

Tensor Decompositions: Uniqueness and Smoothed Analysis

Moses Charikar, Princeton University Semidefinite Optimization, Approximation and Applications ...

lec6 18409 - Tensor Methods (topic models)

lec6 18409 - Tensor Methods (topic models)

Read more details and related context about lec6 18409 - Tensor Methods (topic models).