Sentence examples for more complicated learning from inspiring English sources

These previous studies focused on more complicated learning problems in which the higher-level inferences made through hierarchical Bayesian inference concern very abstract forms of knowledge, although there have also been studies that used Bayesian methods to explain causal inference in perception [29].

These studies demonstrated that the T-maze test was reliable, but possibly not as sensitive as needed, and suggested the need for more complicated learning paradigms for this method (Tanimura 1986).

Although there is a technology aspect in the use of a 3D printer (CAD software being the main one), for many people it's no more complicated than learning how to use a computer or a smartphone for the first time.

The embedded method is slightly more complicated, since the learning method usually decides which features are best for a model while the model is being built [27].

Joseph LeDoux, an expert on brain function and emotion at New York University, likes the work, but cautions that rats in this study may be unusual: "They're dealing with a more complicated form of learning," he says, "so the relevance to our understanding of the amygdala is not so straightforward".

In comparison, in the acute ward, the team had no central role and therefore it might be more complicated to facilitate learning regarding falls.

For example, young domesticated Bengalese finches have a longer window of song learning and so can learn more complicated songs than their wild progenitors, reported biopsychologist Kazuo Okanoya of the University of Tokyo.

This would pose a certain challenge for teachers, requiring them to collaborate with colleagues in their own institutions (being a little more complicated than if the learning outcomes all came from the same module).

Hinton had included a "hidden layer" of neurons that allowed a new generation of networks to learn more complicated functions (like the exclusive-or that had bedeviled the original Perceptron).

Reflecting on errors may be especially important when starting to learn more complicated subjects such as algebra.

In the case of Bayesian network (a generative model), the performance degraded when we tried MaxNrOfParent > 1, which relaxed the number of parents and learned more complicated network structures (data not shown).