7 citations · 13 across the 6 of their papers we have counts for
6 papers
SUPER: Sparse signals with Unknown Phases Efficiently Recovered
Sheng Cai, Mayank Bakshi, Sidharth Jaggi +1
Suppose is any exactly -sparse vector in . We present a class of phase measurement matrix in , and a corresponding algorith…
FRANTIC: A Fast Reference-based Algorithm for Network Tomography via Compressive Sensing
Sheng Cai, Mayank Bakshi, Sidharth Jaggi +1
We study the problem of link and node delay estimation in undirected networks when at most k out of n links or nodes in the network are congested. Our approach relies on end-to-end…
GROTESQUE: Noisy Group Testing (Quick and Efficient)
Sheng Cai, Mohammad Jahangoshahi, Mayank Bakshi +1
Group-testing refers to the problem of identifying (with high probability) a (small) subset of defectives from a (large) set of items via a "small" number of "pooled" tests…
Near-Optimal Stochastic Threshold Group Testing
Chun Lam Chan, Sheng Cai, Mayank Bakshi +2
We formulate and analyze a stochastic threshold group testing problem motivated by biological applications. Here a set of items contains a subset of defective items.…
SHO-FA: Robust compressive sensing with order-optimal complexity, measurements, and bits
Mayank Bakshi, Sidharth Jaggi, Sheng Cai +1
Suppose x is any exactly k-sparse vector in R^n. We present a class of sparse matrices A, and a corresponding algorithm that we call SHO-FA (for Short and Fast) that, with high pro…
Secure Compressed Reading in Smart Grids
Sheng Cai, Jihang Ye, Minghua Chen +2
Smart Grids measure energy usage in real-time and tailor supply and delivery accordingly, in order to improve power transmission and distribution. For the grids to operate effectiv…