163 citations · 704 across the 74 of their papers we have counts for
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stat.ML2014
Beyond L2-Loss Functions for Learning Sparse Models
Karthikeyan Natesan Ramamurthy, Aleksandr Y. Aravkin, Jayaraman J. Thiagarajan
Incorporating sparsity priors in learning tasks can give rise to simple, and interpretable models for complex high dimensional data. Sparse models have found widespread use in stru…
stat.ML2014★ 8 cited
Sparse Quantile Huber Regression for Efficient and Robust Estimation
Aleksandr Y. Aravkin, Anju Kambadur, Aurelie C. Lozano +1
We consider new formulations and methods for sparse quantile regression in the high-dimensional setting. Quantile regression plays an important role in many applications, including…