Sparse Signal Detection with Binary Outcomes
In this talk, I will discuss three examples of sparse signal detection problems in the context of binary outcomes. These will be motivated by examples from next generation sequencing association studies, understanding heterogeneities in large scale networks, and exploring opinion distributions over networks. Moreover, these three examples will serve as templates to explore interesting phase transitions present in such studies. In particular, these phase transitions will be aimed at revealing a difference between studies with possibly dependent binary outcomes and Gaussian outcomes. The theoretical developments will be further complemented with numerical results.
This talk is based on joint works with Xihong Lin, Sumit Mukherjee, Natesh Pillai, Subhabrata Sen, and Ming Yuan.