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20132022
most citedA Parallel Stochastic Approximation Method for Nonconvex Multi-Agent Optimization Problems

112 citations · 910 across the 35 of their papers we have counts for

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Showing 2015Show all

6 papers · 1 filter

stat.AP2015★ 63 cited

Performance Analysis of the Decentralized Eigendecomposition and ESPRIT Algorithm

W. Suleiman, M. Pesavento, A. M. Zoubir

In this paper, we consider performance analysis of the decentralized power method for the eigendecomposition of the sample covariance matrix based on the averaging consensus protoc…

cs.IT2015

Apply Artificial Noise To Secure Fading Relay Networks: A SER-Based Approach

Ying Liu, Liang Li, George C. Alexandropoulos +1

We apply the concept of artificial and controlled interference in a triangular relay network with an untrusted relay aiming at enhancing the wireless communication secrecy between…

math.OC2015★ 93 cited

A Unified Successive Pseudo-Convex Approximation Framework

Yang Yang, Marius Pesavento

In this paper, we propose a successive pseudo-convex approximation algorithm to efficiently compute stationary points for a large class of possibly nonconvex optimization problems.…

math.OC2015★ 13 cited

An Online Parallel and Distributed Algorithm for Recursive Estimation of Sparse Signals

Yang Yang, Mengyi Zhang, Marius Pesavento +1

In this paper, we consider a recursive estimation problem for linear regression where the signal to be estimated admits a sparse representation and measurement samples are only seq…

cs.IT2015★ 15 cited

Rank-Two Beamforming and Power Allocation in Multicasting Relay Networks

Adrian Schad, Ka L. Law, Marius Pesavento

In this paper, we propose a novel single-group multicasting relay beamforming scheme. We assume a source that transmits common messages via multiple amplify-and-forward relays to m…

cs.IT2015★ 19 cited

General Rank Multiuser Downlink Beamforming With Shaping Constraints Using Real-valued OSTBC

Ka Lung Law, Xin Wen, Minh Thanh Vu +1

In this paper we consider optimal multiuser downlink beamforming in the presence of a massive number of arbitrary quadratic shaping constraints. We combine beamforming with full-ra…