Statistical Inference for High-Dimensional Generalized Linear Models with Binary Outcomes
Tony Cai, Zijian Guo, and Rong Ma
The theoretical analysis provides important insights on the adaptivity of optimal confidence intervals with respect to the sparsity of the regression vector. New lower bound techniques are introduced and they can be of independent interest to solve other inference problems in high-dimensional binary GLMs.