989 citations · 6.1k across the 184 of their papers we have counts for
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Tensor decompositions for learning latent variable models
Anima Anandkumar, Rong Ge, Daniel Hsu +2
This work considers a computationally and statistically efficient parameter estimation method for a wide class of latent variable models---including Gaussian mixture models, hidden…
Learning mixtures of spherical Gaussians: moment methods and spectral decompositions
Daniel Hsu, Sham M. Kakade
This work provides a computationally efficient and statistically consistent moment-based estimator for mixtures of spherical Gaussians. Under the condition that component means are…
A Spectral Algorithm for Latent Dirichlet Allocation
Animashree Anandkumar, Dean P. Foster, Daniel Hsu +2
The problem of topic modeling can be seen as a generalization of the clustering problem, in that it posits that observations are generated due to multiple latent factors (e.g., the…
A Method of Moments for Mixture Models and Hidden Markov Models
Animashree Anandkumar, Daniel Hsu, Sham M. Kakade
Mixture models are a fundamental tool in applied statistics and machine learning for treating data taken from multiple subpopulations. The current practice for estimating the param…
Towards minimax policies for online linear optimization with bandit feedback
Sébastien Bubeck, Nicolò Cesa-Bianchi, Sham M. Kakade
We address the online linear optimization problem with bandit feedback. Our contribution is twofold. First, we provide an algorithm (based on exponential weights) with a regret of…