Algorithmic paradigms are:
General approaches to the construction of efficient solutions to problems
Any basic, commonly used approach in designing algorithms could be considered an algorithmic paradigm:
Divide and Conquer
Idea: Divide problem instance into smaller sub-instances of the same problem, solve these recursively, and then put solutions together to a solution of the given instance.
Examples: Mergesort, Quicksort, Strassen’s algorithm, FFT.
Idea: Find solution by always making the choice that looks optimal at the moment — don’t look ahead, never go back.
Examples: Prim’s algorithm, Kruskal’s algorithm.
Idea: Turn recursion upside down.
Example: Floyd-Warshall algorithm for the all pairs shortest path problem.
The word paradigm does translate to example, but that's not how it's used in a scientific context. Your examples are all examples of algorithms (except the travelling salesman problem, which is a NP-hard problem), none of which is trivial enough to be considered an algorithmic paradigm.