Tensor Methods For Learning Latent Variable Models Theory And Practice

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Learning Overcomplete Latent Variable Models through Tensor Power Method

Tensor Decompositions for Learning Hidden Variable Models

Principled Approaches for Learning Latent Variable Models

Spectral Algorithms for Learning Latent Variable Models

DeepMind x UCL | Deep Learning Lectures | 11/12 | Modern Latent Variable Models

Tensor methods for largescale unsupervised learning applications to topic and community modeling

Anima Anandkumar: Tensor methods for training neural networks

Tensor Decompositions: Uniqueness and Smoothed Analysis

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

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Last Updated: October 2, 2026

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Animashree Anandkumar, UC Irvine Spectral Algorithms: From Daniel Hsu, Columbia University simons.berkeley.edu/talks/daniel-hsu-01-27-2017-2 Foundations of Machine Sham Kakade, Microsoft Research New England Rong Ge, Microsoft Research Semidefinite Optimization, Approximation and Applications ... In many applications, we face the challenge of This lecture, by DeepMind Research Scientist Andriy Mnih, explores Talk at Strata 2015 at the Hardcore Data Science Track. Moses Charikar, Princeton University Semidefinite Optimization, Approximation and Applications ...

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