I have come into the stats/machine learning field due to a sideways shift from computational physics. I'm not in an academic environment at the moment but feel as though I achieve good practical results even if they way I work is a bit of a hack; I need results rather than theoretical rigour (not that I'm suggesting theoretical rigour is a bad thing). My knowledge of the literature in the field is not comprehensive, so I often feel I'm reinventing a wheel that must have been published somewhere.
Anyway, that long winded intro is just to give this question some context. I've developed/am developing a technique (or a series of techniques) for optimising hyper-parameters for machine learning algorithms. It seems to produce better results and run more efficiently than what I understand are standard approaches, based on some literature I have read published in the last year or two. I would like to know if a similar approach has in fact been published, since there may be some improvements I've yet to work out myself. I'd also like to know if there is some obvious flaw that I'm not seeing in the approach.
So, I could ask a question along these lines in the main site, but I'm not sure how appropriate it would be for the site. I am concerned that in order to give sufficient details, the question would be very long, essentially a mini academic paper and therefore so specific that is doesn't contribute to a good database of Q&As, even if I receive good answers that help me. It may require a significant investment of time for people to read and comprehend for content that could turn out to be flawed or simply banal. I'm also very slightly concerned that if this is in fact a useful idea then the question may prejudice any later attempts to publish. I don't think that's too likely though, it's not exactly an earth shattering result.
Generally speaking, are questions along the lines of "Here is a new idea I have, is it any good?" useful and appropriate questions here?