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It is helpful for alleviating the data sparsity problem caused by version division.
Experimental results have demonstrated that our approach performs more efficiently than existing methods with respect to accuracy, as well as alleviating the data sparsity and cold-start issues.
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To alleviate the data sparsity problem in under-resourced languages, speaker and language factorization (SLF) technique can be used [34].
To alleviate the data association problem, the tracking also relies on the prior knowledge about the object dynamics, which constrains the feasible associations between detections and objects.
This may alleviate the data movement penalty, requiring data to move only across NUMA domains within a compute node (or perhaps not at all), the speed of which would be significantly faster than moving across the interconnect.
Unlabeled data partially alleviates the training data scarcity problem, thus improves the efficiency of support vector machine (SVM) active learning.
In addition, to alleviate the small data issue of remote sensing images for training, our proposal introduces a self-learning by learning the mapping function using images and their transformed copies.
Methods have been proposed for learning based on a kernel function from a mixture of labeled and unlabeled data [24], alleviating the problem of small-sized training data.
The reluctance to share might be counteracted by covering the entire data management infrastructure with appropriate funding and by intelligent software systems alleviating the task of making data shareable.
For example, combining the data across channels and frequencies within a subject, we can assess when information for emotion discrimination becomes available, effectively reducing the dimensions of the data and alleviating the multiple comparison problem.
In-network processing, compression and approximation are therefore used to ensure that only strictly useful data are exchanged by Things, alleviating the need for many simultaneous data streams.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com