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A Greedy Homotopy Method for Regression with Nonconvex Constraints
Constrained least squares regression is an essential tool for high-dimensional data analysis.
A Comparative Framework for Preconditioned Lasso Algorithms
The Lasso is a cornerstone of modern multivariate data analysis, yet its performance suffers in the common situation in which covariates are correlated.
Bayesian Bias Mitigation for Crowdsourcing
This approach can account for more complex bias patterns that arise in ambiguous or hard labeling tasks and allows us to merge data curation and learning into a single computation.
Heavy-Tailed Process Priors for Selective Shrinkage
Heavy-tailed distributions are often used to enhance the robustness of regression and classification methods to outliers in output space.
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