Sentence examples for learning characterized by from inspiring English sources
The process can be categorized as implicit learning which is defined as a nonconscious form of learning characterized by behavioral improvement [ 43].
We propose an approach to this problem and describe the underlying theory, based on the unsupervised, automatic learning of a "good" representation for supervised learning, characterized by small sample complexity.
One commonality among these technologies is their potential value in supporting a constructivist approach to learning, characterized by the active discovery of knowledge through reflection of experiences with one's environment, the connection of new knowledge to prior knowledge, and interaction with others (Boghossian, 2006; Clements, 2015).
We chose to focus on habituation behavior, which is a form of non-associative learning characterized by reduced response to a repeated stimulus [ 17].
Delusional beliefs can be conceptualized as a learning deficit, characterized by the failure to use contradictory evidence to modify the belief.
The paper by Tommasi [114] addresses the transfer learning environment characterized by limited labeled target data and multiple labeled source domains where each source corresponds to a particular class.
Neuronal branching can actually be stimulated by a stimuli-rich, "secure" learning context characterized by collaboration and mutual support, eliciting motivation and providing for contextually embedded information [ 15, 16].
A learning effect, characterized by an improvement of the performances (latency to fall) over the three trials, was observed for both the 129SVE and C57 strains (trial effect: C57: F2,51=7.001, P=0.001; FVB: F2,51=6.083, P=0.005), but not for the 129SVE strain.
As with human motor skill learning, birdsong learning is characterized by gradual improvements in performance (similarity to the tutor song) and decreased motor variability (Tchernichovski et al., 2001; Ölveczky et al., 2011).
The present phase of Machine Learning is characterized by supervised learning algorithms relying on large sets of labeled examples (n→∞).
In this perspective, concepts like working memory, inhibition, and even timing problems may be too wide concepts to identify the underlying learning style, because a learning style characterized by inefficient chunking or development of entire behavioural sequences may be manifest in different domains in different individuals.
