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A Comparison of Variable Selection Methods for Blockwise Diagonal Designs
Lasso is a celebrated method for variable selection in linear models, but it faces challenges when the covariates are moderately or strongly correlated.
Learning and Optimization with Seasonal Patterns
We show that our learning policy incurs a regret upper bound $\tilde{O}(\sqrt{T\sum_{k=1}^K T_k})$ where $T_k$ is the period of arm $k$.
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