Somewhat related: I am quite fond of Chris Okasaki's "Purely Functional Data Structures" and "Concrete Math" by R. Graham, D. Knuth, and O. Patashnik.
But I have almost the exact opposite qualm about most books from what you air: I can't have enough precision. I agree that there can be too many technical details, but there can't be too much precision.
If CS undergrads can't take it, they deserve to suffer. There's always vocational training for people who want a focus on applications. Try to become e.g. a Fachinformatiker (http://de.wikipedia.org/wiki/Fachinformatiker).
P.S. I guess I am a bit too harsh. I agree with most of your points.
> I could have learnt all these algorithms, if I didn't need to chew through all that theoretical packaging and generalization. Instead I spend all my time to dig through precise definitions just to get one or two concepts, when I could have gotten them all, if representation was good enough.
Precise definitions can help your understanding. I hope you will some day get a professor who uses them to good effect.
> Learning is ineffective when you compare one algorithm with a blurred idea of another.
Isn't this a good argument to learn many algorithms with precision?
> I might sound like a confused student, but what I'm trying to say is that there should be one unified, simple and consistent source of algorithms in understandable languages.
Go, write one, please!
> I have the large algorithm encyclopedia from Springer Verlag, and it polluted with all uncertainties of the modern CS studies.
Are you talking about "The Algorithm Design Manual" from Skiena? I co-worker brought it to the office recently. I can't bring myself to like it. It seems there are too many references and not enough meat. I have fonder memories of Sedgewick's "Algorithms". But that may be nostalgia. (Get the version in C or the original Pascal.)
Feel free to ask me about algorithms or data structures, my email address is in my profile. I enjoy talking about algorithms way too much for my own good.