Issue Many max-tree algorithms, some of them being specific to a dedicated task (e.g. filtering) Goal Comparisons of max-tree algorithms have been attempted, but they are partial. Contribution Provide a full and fair comparison of 5 max-tree algorithms and some variations in a common framework, i.e., same hardware, same language (C++) and same outputs.

is a computationally attractive alternative to standard covariance selection for sparse high-dimensional graphs. Neighborhood selection estimates the conditional independence restrictions separately for each node in the graph and is hence equivalent to variable selection for Gaussian linear models. We

Abstract — The cooperative utilization of antenna diversity among closely-located nodes is referred to as node cooperation or cooperative diversity. To realize this, a group of nodes are first to form a cluster, which necessitates a node selection algorithm. We propose a few node selection

group of receiver nodes are first to form a cluster, which necessitates a node selection algorithm. The operation of such node selection is similar to antenna selection in multiple-input multiple-output (MIMO) systems, except that relaying (or cooperation) cost should be considered. We propose a few

The study of node-selection query languages for (finite) trees has been a major topic in the recent research on query languages for Web documents. On one hand, there has been an extensive study of XPath and its various extensions. On the other hand, query languages based on classical logics

feature selection in small sample size situations. Index Terms—Feature selection, curse of dimensionality, genetic algorithm, node pruning, texture models, SAR image classification. 1

In genetic programming, the reproductive operators of cross-over and mutation both require the selection of nodes from the reproducing individuals. Both unbiased random selec-tion and Koza 90/10 mechanisms remain popular, despite their arbitrary natures and a lack of evidence for their ef

of the network’s performance and QoS. Thus, distributed boundary node selection algorithms (BNS-Algorithms) are proposed to address these issues. BNS-algorithms allow B-nodes to self-select based on available 1-hop information extracted from nodes ’ simple geometrical and statistical features. Our results show

A central problem in executing performance critical parallel and distributed applications on shared networks is the selection of computation nodes and communication paths for execution. Automatic selection of nodes is complex as the best choice depends on the application structure as well

proposed approach does not make any assumptions about the presence of infrastructure or about node capabilities, other than the availability of multiple power levels in sensor nodes. We present a protocol, HEED (Hybrid Energy-Efficient Distributed clustering), that periodically selects cluster heads