Diffusion Adaptation Strategies for Distributed Optimization and Learning Over Networks
出版年份 2012 全文链接
标题
Diffusion Adaptation Strategies for Distributed Optimization and Learning Over Networks
作者
关键词
-
出版物
IEEE TRANSACTIONS ON SIGNAL PROCESSING
Volume 60, Issue 8, Pages 4289-4305
出版商
Institute of Electrical and Electronics Engineers (IEEE)
发表日期
2012-07-11
DOI
10.1109/tsp.2012.2198470
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- (2011) Sheng-Yuan Tu et al. IEEE Journal of Selected Topics in Signal Processing
- Convergence Rate Analysis of Distributed Gossip (Linear Parameter) Estimation: Fundamental Limits and Tradeoffs
- (2011) Soummya Kar et al. IEEE Journal of Selected Topics in Signal Processing
- Distributed Asynchronous Constrained Stochastic Optimization
- (2011) Kunal Srivastava et al. IEEE Journal of Selected Topics in Signal Processing
- Modeling Bird Flight Formations Using Diffusion Adaptation
- (2011) Federico S. Cattivelli et al. IEEE TRANSACTIONS ON SIGNAL PROCESSING
- Adaptive Robust Distributed Learning in Diffusion Sensor Networks
- (2011) Symeon Chouvardas et al. IEEE TRANSACTIONS ON SIGNAL PROCESSING
- Regression shrinkage and selection via the lasso: a retrospective
- (2011) Robert Tibshirani JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY
- Adaptive Learning in a World of Projections
- (2010) Sergios Theodoridis et al. IEEE SIGNAL PROCESSING MAGAZINE
- Diffusion Strategies for Distributed Kalman Filtering and Smoothing
- (2010) Federico S. Cattivelli et al. IEEE TRANSACTIONS ON AUTOMATIC CONTROL
- Decentralized Parameter Estimation by Consensus Based Stochastic Approximation
- (2010) Srdjan S. Stankovic et al. IEEE TRANSACTIONS ON AUTOMATIC CONTROL
- Diffusion Least-Mean Squares With Adaptive Combiners: Formulation and Performance Analysis
- (2010) N Takahashi et al. IEEE TRANSACTIONS ON SIGNAL PROCESSING
- Distributed Sparse Linear Regression
- (2010) Gonzalo Mateos et al. IEEE TRANSACTIONS ON SIGNAL PROCESSING
- Online Sparse System Identification and Signal Reconstruction Using Projections Onto Weighted $\ell_{1}$ Balls
- (2010) Yannis Kopsinis et al. IEEE TRANSACTIONS ON SIGNAL PROCESSING
- Distributed Stochastic Subgradient Projection Algorithms for Convex Optimization
- (2010) S. Sundhar Ram et al. JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS
- Gossip Algorithms for Distributed Signal Processing
- (2010) Alexandros G. Dimakis et al. PROCEEDINGS OF THE IEEE
- Distributed Subgradient Methods for Multi-Agent Optimization
- (2009) Angelia Nedic et al. IEEE TRANSACTIONS ON AUTOMATIC CONTROL
- Broadcast Gossip Algorithms for Consensus
- (2009) T.C. Aysal et al. IEEE TRANSACTIONS ON SIGNAL PROCESSING
- Fast Distributed Average Consensus Algorithms Based on Advection-Diffusion Processes
- (2009) S. Sardellitti et al. IEEE TRANSACTIONS ON SIGNAL PROCESSING
- Diffusion LMS Strategies for Distributed Estimation
- (2009) F.S. Cattivelli et al. IEEE TRANSACTIONS ON SIGNAL PROCESSING
- Improving the Tracking Capability of Adaptive Filters via Convex Combination
- (2008) Magno T. M. Silva et al. IEEE TRANSACTIONS ON SIGNAL PROCESSING
- Diffusion recursive least-squares for distributed estimation over adaptive networks
- (2008) F.S. Cattivelli et al. IEEE TRANSACTIONS ON SIGNAL PROCESSING
- Diffusion Least-Mean Squares Over Adaptive Networks: Formulation and Performance Analysis
- (2008) Cassio G. Lopes et al. IEEE TRANSACTIONS ON SIGNAL PROCESSING
- Sensor Networks With Random Links: Topology Design for Distributed Consensus
- (2008) S. Kar et al. IEEE TRANSACTIONS ON SIGNAL PROCESSING
- Enhancing Sparsity by Reweighted ℓ 1 Minimization
- (2008) Emmanuel J. Candès et al. JOURNAL OF FOURIER ANALYSIS AND APPLICATIONS
- Consensus in Ad Hoc WSNs With Noisy Links—Part I: Distributed Estimation of Deterministic Signals
- (2007) Ioannis D. Schizas et al. IEEE TRANSACTIONS ON SIGNAL PROCESSING
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