163 citations · 704 across the 74 of their papers we have counts for
4 papers · 1 filter
Robust EM kernel-based methods for linear system identification
Giulio Bottegal, Aleksandr Y. Aravkin, Håkan Hjalmarsson +1
Recent developments in system identification have brought attention to regularized kernel-based methods. This type of approach has been proven to compare favorably with classic par…
A variational approach to stable principal component pursuit
Aleksandr Aravkin, Stephen Becker, Volkan Cevher +1
We introduce a new convex formulation for stable principal component pursuit (SPCP) to decompose noisy signals into low-rank and sparse representations. For numerical solutions of…
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…
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…