Decentralized RLS With Data-Adaptive Censoring for Regressions Over Large-Scale Networks
Decentralized RLS With Data-Adaptive Censoring for Regressions Over Large-Scale Networks
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DOI：
10.1109/tsp.2018.2795594
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发表时间：
2016-12
影响因子：
5.4
通讯作者：
Zifeng Wang;Zheng Yu;Qing Ling;Dimitris Berberidis;G. Giannakis
中科院分区：
文献类型：
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作者：
Zifeng Wang;Zheng Yu;Qing Ling;Dimitris Berberidis;G. Giannakis
网络数据的洪流推动了计算和通信高效信息处理算法的发展。在这种情况下，引入了三种数据自适应审查策略，以显着减少分散递归最小二乘求解器的计算和通信开销。第一个依赖于交替最小化和随机牛顿迭代来最小化网络范围的成本，这会丢弃带有小创新的观察结果。在最终的算法中，每个节点执行本地数据自适应审查以减少计算量，同时与邻居交换其本地估计，以便就网络范围的解决方案达成一致。第二种策略进一步降低了通信成本，当节点对传入数据引起的创新最小时，该策略阻止节点将其本地估计传输到邻居。在第三种策略中，当数据自适应审查生效时，不仅禁止传输来自邻居的估计，而且还禁止接收来自邻居的估计。对于所有策略，提供了一个简单的标准来选择创新阈值以达到规定的平均数据减少。新颖的基于审查的 (C)D-RLS 算法被证明收敛于均根偏差意义上的最优参数。数值实验验证了所提出的算法在减少计算和通信开销方面的有效性。
The deluge of networked data motivates the development of algorithms for computation- and communication-efficient information processing. In this context, three data-adaptive censoring strategies are introduced to considerably reduce the computation and communication overhead of decentralized recursive least-squares solvers. The first relies on alternating minimization and the stochastic Newton iteration to minimize a network-wide cost, which discards observations with small innovations. In the resultant algorithm, each node performs local data-adaptive censoring to reduce computations while exchanging its local estimate with neighbors so as to consent on a network-wide solution. The communication cost is further reduced by the second strategy, which prevents a node from transmitting its local estimate to neighbors when the innovation it induces to incoming data is minimal. In the third strategy, not only transmitting, but also receiving estimates from neighbors is prohibited when data-adaptive censoring is in effect. For all strategies, a simple criterion is provided for selecting the threshold of innovation to reach a prescribed average data reduction. The novel censoring-based (C)D-RLS algorithms are proved convergent to the optimal argument in the mean-root deviation sense. Numerical experiments validate the effectiveness of the proposed algorithms in reducing computation and communication overhead.