A Blockwise Descent Algorithm for Group-penalized Multiresponse and Multinomial Regression
This provides a faster computational tool for researchers in fields like genomics dealing with high-dimensional regression problems.
The authors developed a blockwise descent algorithm for group-penalized multiresponse and multinomial regression, with an R implementation that is an order of magnitude faster than a competing algorithm and can solve gene-expression-sized problems in real time.
In this paper we purpose a blockwise descent algorithm for group-penalized multiresponse regression. Using a quasi-newton framework we extend this to group-penalized multinomial regression. We give a publicly available implementation for these in R, and compare the speed of this algorithm to a competing algorithm --- we show that our implementation is an order of magnitude faster than its competitor, and can solve gene-expression-sized problems in real time.