Sentence examples for finding dependencies from inspiring English sources

The basic problem, not only in the management of autonomous robot, is finding the weights of the connections between neurons, either on the basis of the data (supervised learning) or finding dependencies in the data (unsupervised).

A widely known classical statistical method for finding dependencies between datasets is canonical correlation analysis [CCA; Hotelling, 1936], for which there exist recent sparse variants (Archambeau and Bach, 2009; Parkhomenko et al., 2007; Waaijenborg and Zwinderman, 2007; Witten and Tibshirani, 2009).

Finding dependencies among tasks through provenance queries, without additional support, is not trivial.

Finding dependencies among different types of data could help improve the accuracy.

However, finding the dependencies among programs without the support of a tool is not a trivial activity and, in many cases, becomes a barrier to build more sophisticated models and analysis.

Another research issue is finding appropriate dependency models for natural sounds because the dependency among the frequency components may not be related to the mel-scale.

The results indicate that a part of the vibrations depends on the flow rate of the MQL system and its interaction with the feed rate, finding no dependency on the type of interruption.

This suggests that such source priors do not exactly match the distribution of speech signals and that the IVA performance for speech separation can be improved by finding better dependency models [22, 23].

The internal structure in data can be discovered by identifying "invariants", i.e. by finding (generally implicit) dependencies between variables and parameters in the model.

Further, rather than looking at feature selection as a problem of finding inter-feature dependencies for reducing number of features, we treat each feature individually and arrive at features that would have the ability to contribute to classifiers performance improvement.

The method is capable of finding covariate-related dependencies between the sources.