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Diversity of the vertical distribution of the root systems of different species allows efficient maximization of plant growth and crop yields in unfavorable environments with poor resource mobility, such as infertile or arid fields (Hodge et al. 2009; Rich and Watt 2013).
Our new approach based on additive linear-time subset scanning enables efficient maximization of penalized scan statistics over subsets of the data, thus improving detection of irregular clusters.
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Results are provided for three scenarios: 1. "Purely efficient allocation" (maximization of (4)), 2. "purely equitable allocation" (minimization of (5)), and 3. "half efficient/half equitable allocation" (maximization of (6)).
In both claims, "efficient" means maximization of the social willingness-to-pay.
Federations may facilitate efficient preference maximization more generally, as formalized in the literature on economic and fiscal federalism though many such arguments support decentralization rather than federalism proper.
Using the proposed technique, we derive a computationally efficient expectation maximization (EM) estimator for simultaneous estimation of both SI and communication channels.
For parameter learning of the semisupervised PPLS model, an efficient Expectation-Maximization algorithm is designed.
For training and parameter learning of the probabilistic PLS model, the Bayes rule is applied and an efficient Expectation-Maximization algorithm is designed.
It decouples the inference in each dimension, and can be solved with an efficient expectation-maximization (EM) algorithm that avoids matrix inversion.
First, we present an efficient Expectation-Maximization (EM -based algorithm for EM -basedg the malgorithmposteriori (MAP) parameters ofor PSG, givestimatingor paired-end RNA-Seq dathe
Pei, S., X. Teng, J. Shaman, F. Morone and H.A. Makse, 2017: Efficient collective influence maximization in cascading processes with first-order transitions.
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