Adaptive learning in lasso models
Regression with L1-regularization, Lasso, is a popular algorithm for recovering the sparsity pattern (also known as model selection) in linear models from observations contaminated by noise. We examine a scenario where a fraction of the zero co-variates are highly correlated with non-zero co-variate...
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| Format: | Others |
| Language: | en_US |
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Georgia Institute of Technology
2016
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| Online Access: | http://hdl.handle.net/1853/54353 |