activity
20102022
most citedDistributed Algorithms for Learning and Cognitive Medium Access with Logarithmic Regret

242 citations · 416 across the 24 of their papers we have counts for

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Showing cs.ITShow all

11 papers · 1 filter

cs.IT2022

Task-Aware Network Coding Over Butterfly Network

Jiangnan Cheng, Sandeep Chinchali, Ao Tang

Network coding allows distributed information sources such as sensors to efficiently compress and transmit data to distributed receivers across a bandwidth-limited network. Classic…

cs.IT2012★ 1 cited

Sparse Recovery with Graph Constraints

Meng Wang, Weiyu Xu, Enrique Mallada +1

Sparse recovery can recover sparse signals from a set of underdetermined linear measurements. Motivated by the need to monitor large-scale networks from a limited number of measure…

cs.IT2011★ 22 cited

Sparse Recovery from Nonlinear Measurements with Applications in Bad Data Detection for Power Networks

Weiyu Xu, Meng Wang, Jianfeng Cai +1

In this paper, we consider the problem of sparse recovery from nonlinear measurements, which has applications in state estimation and bad data detection for power networks. An iter…

cs.IT2011★ 2 cited

Sparse Recovery with Graph Constraints: Fundamental Limits and Measurement Construction

Meng Wang, Weiyu Xu, Enrique Mallada +1

This paper addresses the problem of sparse recovery with graph constraints in the sense that we can take additive measurements over nodes only if they induce a connected subgraph.…

cs.IT2011★ 2 cited

On State Estimation with Bad Data Detection

Weiyu Xu, Meng Wang, Ao Tang

In this paper, we consider the problem of state estimation through observations possibly corrupted with both bad data and additive observation noises. A mixed and …

cs.IT2010

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…