30 citations · 81 across the 15 of their papers we have counts for
6 papers · 1 filter
Two-block vs. Multi-block ADMM: An empirical evaluation of convergence
Andre Goncalves, Xiaoli Liu, Arindam Banerjee
Alternating Direction Method of Multipliers (ADMM) has become a widely used optimization method for convex problems, particularly in the context of data mining in which large optim…
DAPPER: Scaling Dynamic Author Persona Topic Model to Billion Word Corpora
Robert Giaquinto, Arindam Banerjee
Extracting common narratives from multi-author dynamic text corpora requires complex models, such as the Dynamic Author Persona (DAP) topic model. However, such models are complex…
Sparse Linear Isotonic Models
Sheng Chen, Arindam Banerjee
In machine learning and data mining, linear models have been widely used to model the response as parametric linear functions of the predictors. To relax such stringent assumptions…
Alternating Estimation for Structured High-Dimensional Multi-Response Models
Sheng Chen, Arindam Banerjee
We consider learning high-dimensional multi-response linear models with structured parameters. By exploiting the noise correlations among responses, we propose an alternating estim…
Structured Stochastic Linear Bandits
Nicholas Johnson, Vidyashankar Sivakumar, Arindam Banerjee
The stochastic linear bandit problem proceeds in rounds where at each round the algorithm selects a vector from a decision set after which it receives a noisy linear loss parameter…
Structured Matrix Recovery via the Generalized Dantzig Selector
Sheng Chen, Arindam Banerjee
In recent years, structured matrix recovery problems have gained considerable attention for its real world applications, such as recommender systems and computer vision. Much of th…