Necessary & Sufficient Conditions for Consistency of Haar Wavelet Expressions to their resizable Hadoop Cluster Channels and Complexity
Journal Title: EAI Endorsed Transactions on Cloud Systems - Year 2017, Vol 3, Issue 9
Abstract
AbstractβWe develop a novel technique for resizable Hadoop clusterβs lower bounds, the bipartite matching rectangular array of Haar Wavelet expressions. Specifically, fix an arbitrary hybrid kernel function π βΆ {π, π}π β {π, π} and let π¨π be the rectangular array of Haar Wavelet expressions whose columns are each an application of π to some subset of the variables ππ, ππ, β¦ , πππ . We prove that π¨π has bounded-capacity resizable Hadoop clusterβs complexity π(π ), where π is the approximate degree of π. This finding remains valid in the MapReduce programming model, regardless of prior measurement. In particular, it gives a new and simple proof of lower bounds for robustness and other symmetric conjunctive predicates. We further characterize the discrepancy, approximate PageRank, and approximate trace distance norm of π¨π in terms of well-studied analytic properties of π, broadly generalizing several findings on small-bias resizable Hadoop cluster and agnostic inference. The method of this paper has also enabled important progress in multi-cloud resizable Hadoop clusterβs complexity.
Authors and Affiliations
Ravinder Prakash G.
Keywords
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- EP ID EP45591
- DOI http://dx.doi.org/10.4108/eai.28-6-2017.153490
- Views 267
- Downloads 0
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