40 citations · 165 across the 10 of their papers we have counts for
6 papers · 1 filter
Distributed Stochastic Subgradient Projection Algorithms for Convex Optimization
S. Sundhar Ram, A. Nedich, V. V. Veeravalli
We consider a distributed multi-agent network system where the goal is to minimize a sum of convex objective functions of the agents subject to a common convex constraint set. Each…
Incremental Stochastic Subgradient Algorithms for Convex Optimization
S Sundhar Ram, A Nedich, V. V. Veeravalli
In this paper we study the effect of stochastic errors on two constrained incremental sub-gradient algorithms. We view the incremental sub-gradient algorithms as decentralized netw…
Low-Complexity Structured Precoding for Spatially Correlated MIMO Channels
Vasanthan Raghavan, Akbar Sayeed, Venu Veeravalli
The focus of this paper is on spatial precoding in correlated multi-antenna channels, where the number of independent data-streams is adapted to trade-off the data-rate with the tr…
Distributed and Recursive Parameter Estimation in Parametrized Linear State-Space Models
S. Sundhar Ram, V. V. Veeravalli, A. Nedic
We consider a network of sensors deployed to sense a spatio-temporal field and estimate a parameter of interest. We are interested in the case where the temporal process sensed by…
Gaussian Interference Networks: Sum Capacity in the Low Interference Regime and New Outer Bounds on the Capacity Region
V. Sreekanth Annapureddy, Venugopal V. Veeravalli
Establishing the capacity region of a Gaussian interference network is an open problem in information theory. Recent progress on this problem has led to the characterization of the…
Sum Capacity of the Gaussian Interference Channel in the Low Interference Regime
V. Sreekanth Annapureddy, Venugopal V. Veeravalli
New upper bounds on the sum capacity of the two-user Gaussian interference channel are derived. Using these bounds, it is shown that treating interference as noise achieves the sum…