163 citations · 704 across the 74 of their papers we have counts for
5 papers · 2 filters
A SMART Stochastic Algorithm for Nonconvex Optimization with Applications to Robust Machine Learning
Aleksandr Aravkin, Damek Davis
In this paper, we show how to transform any optimization problem that arises from fitting a machine learning model into one that (1) detects and removes contaminated data from the…
Boosting as a kernel-based method
Aleksandr Y. Aravkin, Giulio Bottegal, Gianluigi Pillonetto
Boosting combines weak (biased) learners to obtain effective learning algorithms for classification and prediction. In this paper, we show a connection between boosting and kernel-…
A General Family of Trimmed Estimators for Robust High-dimensional Data Analysis
Eunho Yang, Aurelie Lozano, Aleksandr Aravkin
We consider the problem of robustifying high-dimensional structured estimation. Robust techniques are key in real-world applications which often involve outliers and data corruptio…
Dynamic matrix factorization with social influence
Aleksandr Y. Aravkin, Kush R. Varshney, Liu Yang
Matrix factorization is a key component of collaborative filtering-based recommendation systems because it allows us to complete sparse user-by-item ratings matrices under a low-ra…
Dual Smoothing and Level Set Techniques for Variational Matrix Decomposition
Aleksandr Y. Aravkin, Stephen Becker
We focus on the robust principal component analysis (RPCA) problem, and review a range of old and new convex formulations for the problem and its variants. We then review dual smoo…