1 citations · 1 across the 4 of their papers we have counts for
4 papers
Many-User Multiple Access with Random User Activity: Achievability Bounds and Efficient Schemes
Xiaoqi Liu, Pablo Pascual Cobo, Ramji Venkataramanan
We study the Gaussian multiple access channel with random user activity, in the regime where the number of users is proportional to the code length. The receiver may know some stat…
Inferring Change Points in High-Dimensional Regression via Approximate Message Passing
Gabriel Arpino, Xiaoqi Liu, Julia Gontarek +1
We consider the problem of localizing change points in a generalized linear model (GLM), a model that covers many widely studied problems in statistical learning including linear,…
Coded Many-User Multiple Access via Approximate Message Passing
Xiaoqi Liu, Kuan Hsieh, Ramji Venkataramanan
We consider communication over the Gaussian multiple-access channel in the regime where the number of users grows linearly with the codelength. In this regime, schemes based on spa…
Sketching sparse low-rank matrices with near-optimal sample- and time-complexity using message passing
Xiaoqi Liu, Ramji Venkataramanan
We consider the problem of recovering an low-rank matrix with -sparse singular vectors from a small number of linear measurements (sketch). We propose a sketchi…