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Compared to traditional philosphical discussions of inductive inference, learning theory provides a radically new way of thinking about induction and scientific method.
In contrast to other philosophical approaches to inductive inference, learning theory does not aim to describe a universal inductive method or explicate general axioms of inductive rationality.
Mobile cloud computing technologies is also included in their proposed architecture incorporating a cognitive Internet of Things (IoT) engine that interacts with a cloud-based engine for reconfiguration, inference, learning, and orientation.
This Bayesian observer assumption provides principled constraints on the computations that may underlie perceptual inference, learning and decision-making.
Resource provisioning, task classification and allocation, resource release and update, and inference learning are all performed by this module.
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Consequently, they are crucial to such psychological processes as categorization, inference, memory, learning, and decision-making.
The mapping is achieved by the context perception layer through computation, inference and learning techniques.
We can draw the inference on learning habits analyzing the distribution of downloads before the test.
Composite context on the other hand can be derived from atomic context elements through computation, inference, or learning techniques.
While we infer that Tweety flies on the basis of the information that Tweety is a bird and the background knowledge that birds usually fly, we have good reasons to retract this inference when learning that Tweety is a penguin or a kiwi.
The clique-tree technique and the variable-elimination technique were implemented for efficient inference and learning [11], [20], [25].
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