242 citations · 416 across the 24 of their papers we have counts for
7 papers · 1 filter
On the Performance of Sparse Recovery via L_p-minimization (0<=p <=1)
Meng Wang, Weiyu Xu, Ao Tang
It is known that a high-dimensional sparse vector x* in R^n can be recovered from low-dimensional measurements y= A^{m*n} x* (m<n) . In this paper, we investigate the recovering ab…
A Generalized Coupon Collector Problem
Weiyu Xu, Ao Kevin Tang
This paper provides analysis to a generalized version of the coupon collector problem, in which the collector gets distinct coupons each run and she chooses the one that she ha…
On the Scaling Law for Compressive Sensing and its Applications
Weiyu Xu, Ao Tang
minimization can be used to recover sufficiently sparse unknown signals from compressed linear measurements. In fact, exact thresholds on the sparsity (the size of the sup…
Compressive Sensing over Graphs
Weiyu Xu, Enrique Mallada, Ao Tang
In this paper, motivated by network inference and tomography applications, we study the problem of compressive sensing for sparse signal vectors over graphs. In particular, we are…
Distributed Algorithms for Learning and Cognitive Medium Access with Logarithmic Regret
Animashree Anandkumar, Nithin Michael, Ao Kevin Tang +1
The problem of distributed learning and channel access is considered in a cognitive network with multiple secondary users. The availability statistics of the channels are initially…
The Limits of Error Correction with lp Decoding
Meng Wang, Weiyu Xu, Ao Tang
An unknown vector f in R^n can be recovered from corrupted measurements y = Af + e where A^(m*n)(m>n) is the coding matrix if the unknown error vector e is sparse. We investigate t…