1.7k citations · 1.9k across the 17 of their papers we have counts for
18 papers
Group COMBSS: Group Selection via Continuous Optimization
Anant Mathur, Sarat Moka, Benoit Liquet +1
We present a new optimization method for the group selection problem in linear regression. In this problem, predictors are assumed to have a natural group structure and the goal is…
Generalized Linear Models via the Lasso: To Scale or Not to Scale?
Anant Mathur, Sarat Moka, Zdravko Botev
The Lasso regression is a popular regularization method for feature selection in statistics. Prior to computing the Lasso estimator in both linear and generalized linear models, it…
Column Subset Selection and Nyström Approximation via Continuous Optimization
Anant Mathur, Sarat Moka, Zdravko Botev
We propose a continuous optimization algorithm for the Column Subset Selection Problem (CSSP) and Nyström approximation. The CSSP and Nyström method construct low-rank approximatio…
Estimation When Both Covariance And Precision Matrices Are Sparse
Shev Macnamara, Erik Schlögl, Zdravko I. Botev
We offer a method to estimate a covariance matrix in the special case that \textit{both} the covariance matrix and the precision matrix are sparse --- a constraint we call double s…
Variance Reduction for Matrix Computations with Applications to Gaussian Processes
Anant Mathur, Sarat Moka, Zdravko Botev
In addition to recent developments in computing speed and memory, methodological advances have contributed to significant gains in the performance of stochastic simulation. In this…
Sampling Conditionally on a Rare Event via Generalized Splitting
Zdravko I. Botev, Pierre L'Ecuyer
We propose and analyze a generalized splitting method to sample approximately from a distribution conditional on the occurrence of a rare event. This has important applications in…