3 papers
stat.CO2026
Efficient Solvers for SLOPE in R, Python, Julia, and C++
Johan Larsson, Malgorzata Bogdan, Krystyna Grzesiak +2
We present a suite of packages in R, Python, Julia, and C++ that efficiently solve the Sorted L-One Penalized Estimation (SLOPE) problem. The packages feature a highly efficient hy…
math.ST2026
Asymptotic Theory for Graphical SLOPE: Precision Estimation and Pattern Convergence
Ivan Hejný, Giovanni Bonaccolto, Philipp Kremer +3
This paper studies Graphical SLOPE for precision matrix estimation, with emphasis on its ability to recover both sparsity and clusters of edges with equal or similar strength. In a…
stat.ML2025
The Choice of Normalization Influences Shrinkage in Regularized Regression
Johan Larsson, Jonas Wallin
Regularized models are often sensitive to the scales of the features in the data and it has therefore become standard practice to normalize (center and scale) the features before f…