Sentence examples for by using a learned from inspiring English sources

Next, we removed unreliable lowly expressed transcripts by using a learned read coverage threshold similar to previous study [ 28].

Yin et al. [31] exploited the hierarchical structure in document images and presented a bottom-up grouping method: CCs of an input image were grouped into textlines by using a learned metric.

In the learning phase a model that represents the best distribution of the involved codewords in each category of scenes was built by using a learning algorithm based on Latent Dirichlet Allocation [35].

In this work, we improved this technique by using a learning schema, namely the Exploration-Exploitation using Exponential weight (EXP3), that allows smart resource allocations.

This can be realized by using a learning algorithm to associate the "predictiveness strength" of a network with the assessment of the accuracy of the learning algorithm trained on the network itself.

The solution presents a clear improvement on a tracking algorithm achieved by using a machine learning approach for visual object detection and recognition fordata association.

We aimed to evaluate the neuronal networks that support naming in TLE by using a machine learning algorithm intended to predict naming performance in subjects with medication refractory TLE using only the structural brain connectome reconstructed from diffusion tensor imaging.

One study looking at 4041 patients with depression, found that by using a machine learning approach, they could predict response to the antidepressant citalopram with a highly statistically significant accuracy of 64.6%.

Carter et al. [19], by using a machine learning approach based on differences in compositional and structural parameters present in known RNAs compared to non-coding sequences, achieved an improvement in RNA genes identification in bacterial and archaeal genomes.

Here we report our approach for improving INDEL calling accuracy by using a machine learning algorithm to combine call sets generated with three independent methods, and by leveraging the strengths of each individual pipeline.

In this paper, we propose a new transfer learning framework for recommender systems, which relaxes the above assumption to facilitate flexible knowledge transfer across different systems with low cost by using an active learning principle to construct entity correspondences across systems.