2 citations · 2 across the 1 of their papers we have counts for
2 papers
math.ST2025
Learning sparse generalized linear models with binary outcomes via iterative hard thresholding
Namiko Matsumoto, Arya Mazumdar
In statistics, generalized linear models (GLMs) are widely used for modeling data and can expressively capture potential nonlinear dependence of the model's outcomes on its covaria…
cs.IT2022★ 2 cited
Improved Support Recovery in Universal One-bit Compressed Sensing
Namiko Matsumoto, Arya Mazumdar, Soumyabrata Pal
One-bit compressed sensing (1bCS) is an extremely quantized signal acquisition method that has been proposed and studied rigorously in the past decade. In 1bCS, linear samples of a…