Minimization methods for non-differentiable functions
Minimization methods for non-differentiable functions
Topics in matrix analysis
Adaptive filter theory (2nd ed.)
Adaptive filter theory (2nd ed.)
Matrix computations (3rd ed.)
Parallel and Distributed Computation: Numerical Methods
Parallel and Distributed Computation: Numerical Methods
Vector Space Projections: A Numerical Approach to Signal and Image Processing, Neural Nets, and Optics
Constrained Adaptive Linear Multiuser Detection Schemes
Journal of VLSI Signal Processing Systems
Convex Optimization
IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
An Iterative MPEG Super-Resolution with an Outer Approximation of Framewise Quantization Constraint
IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
Distributed average consensus with least-mean-square deviation
Journal of Parallel and Distributed Computing
A Convergent Incremental Gradient Method with a Constant Step Size
SIAM Journal on Optimization
Adaptive Filters
Adaptive Processing over Distributed Networks
IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
Learning in diffusion networks with an adaptive projected subgradient method
ICASSP '09 Proceedings of the 2009 IEEE International Conference on Acoustics, Speech and Signal Processing
IEEE Transactions on Signal Processing
Diffusion Least-Mean Squares Over Adaptive Networks: Formulation and Performance Analysis
IEEE Transactions on Signal Processing - Part II
Convergence analysis of the binormalized data-reusing LMS algorithm
IEEE Transactions on Signal Processing
Incremental Adaptive Strategies Over Distributed Networks
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
An efficient robust adaptive filtering algorithm based on parallelsubgradient projection techniques
IEEE Transactions on Signal Processing
Online Kernel-Based Classification Using Adaptive Projection Algorithms
IEEE Transactions on Signal Processing - Part I
An Affine Combination of Two LMS Adaptive Filters—Transient Mean-Square Analysis
IEEE Transactions on Signal Processing
Diffusion Recursive Least-Squares for Distributed Estimation Over Adaptive Networks
IEEE Transactions on Signal Processing
Energy-based sensor network source localization via projection onto convex sets
IEEE Transactions on Signal Processing
IEEE Communications Magazine
Convex set theoretic image recovery by extrapolated iterations of parallel subgradient projections
IEEE Transactions on Image Processing
A unified view of adaptive variable-metric projection algorithms
EURASIP Journal on Advances in Signal Processing
Distributed multiagent learning with a broadcast adaptive subgradient method
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1
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We present an algorithm that minimizes asymptotically a sequence of nonnegative convex functions over diffusion networks. In the proposed algorithm, at each iteration the nodes in the network have only partial information of the cost function, but they are able to achieve consensus on a possible minimizer asymptotically. To account for possible node failures, position changes, and/or reachability problems (because of moving obstacles, jammers, etc.), the algorithm can cope with changing network topologies and cost functions, a desirable feature in online algorithms where information arrives sequentially. Many projection-based algorithms can be straightforwardly extended to (probabilistic) diffusion networks with the proposed scheme. The system identification problem in distributed networks is given as one example of a possible application.