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Found 4 papers, 1 papers with code
High dimensional stochastic linear contextual bandit with missing covariates
Recent works in bandit problems adopted lasso convergence theory in the sequential decision-making setting.
The Sylvester Graphical Lasso (SyGlasso)
We apply the SyGlasso to an electroencephalography (EEG) study to compare the brain connectivity of alcoholic and nonalcoholic subjects.
Precision Matrix Estimation with Noisy and Missing Data
Estimating conditional dependence graphs and precision matrices are some of the most common problems in modern statistics and machine learning.
Minimum Volume Topic Modeling
We propose a new topic modeling procedure that takes advantage of the fact that the Latent Dirichlet Allocation (LDA) log likelihood function is asymptotically equivalent to the logarithm of the volume of the topic simplex.
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