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A conventional MLC transformation solution is based on independently training a single binary classifier for each target label.
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The image patch can be independently trained from every annotated point, and the trained patch is cross-correlated with an image region containing the annotated point.
Prior to coding the privacy policies, the two research assistants were independently trained on a sample of privacy policies (that were not part of the final sample) to use the coding scheme.
In our approach, we independently train CRBMs for each speaker beforehand as shown in Figure 1a.
The ensemble consists of independently trained FFNNs, which contribute to a single prediction.
This can lead to bias leakage where an independently trained AI engine can get influenced (positively or negatively) from another AI engine.
We can build a deep autoencoder by repeating these steps and stacking two or more layers of independently trained sparse autoencoders.
We compared our multi-task methods to SVM models that were independently trained for each target and an SVM model that assumed all targets to be identical.
Our approach is different from this in that we use a separate loss for the RGB, flow, and gating streams, which are independently trained in a sequential way.
Independently trained research nurses unaware of the patient's status (case or control) called each patient and his/her family physician to collect information about associated conditions (diabetes, obesity, dyslipidemia) and drug exposure (amphetamine derivatives), using a semi-structured questionnaire.
Independently trained research assistants collected the data prospectively.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com