6883e621_ws___Machine_Learning__Theory___3
[0] Kernel-based learning [1] You chose a kernel K(x,x’) between datapoints that satisfies certain conditions, and then use it as a measure of similarity when learning. [2] People often find the specification of a similarity function between objects a natural way to incorporate prior information for machine learning problems. Algorithms (like SVMs) for training are reasonably practical—O(n2) for instance. [3] 
Specification of the kernel is not easy for some applications (this is another example of prior elicitation). O(n2) is not efficient enough when there is much data.
All Models of Learning have Flaws « Machine Learning (Theory)
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