Exact(2)
Recognition of speech, and in particular the ability to generalize and learn from small sets of labelled examples like humans do, depends on an appropriate representation of the acoustic input.
The third term is the accumulation of the hinge loss for differently labelled examples whose perimeters are invaded by x i. SVMs [ 46, 47] let to build reliable classifiers in very small sample size problems [ 48] and even may find nonlinear decision boundaries for small training sets.
Similar(58)
Most of the existing feature-based methods and graph-based methods require sufficiently large amount of labeled examples or a fully-labeled graph for training.
Usually a network needs labeled examples to learn effectively.
Machine-learning algorithms need large numbers of labeled examples to learn how to accurately filter data.
So like I said before, they have to be trained on millions of labeled examples.
In many machine learning settings, labeled examples are difficult to collect while unlabeled data are abundant.
Moreover, the number and especially the quality of the manually labeled examples challenge such strategies.
These learning strategies usually require a large set of labeled examples which can be expensive to obtain.
Cox also highlighted how the software requires thousands of labeled examples to recognize a new type of object.
After that, the system was taught to identify sarcasm using an existing data set of labeled examples.
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Justyna Jupowicz-Kozak
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