I’ve been spending a lot of time trying to reach a state in which I’d get a partial Invariance… I observed that there are at least 2 pathways that would lead to different results..
- The frequency and sequence of patterns – only certain sequences would lead to the desired result. There is no way to guarantee for a certain result. The only way to guarantee a result is to have a precise training set which is not what I want, but so far I could not think of a way to correct for an imbalanced training set..
- Timing. Learning depends on time, meaning at time t1 we can have result R1 and at time t2 (where t2>>t1), we have a result R2. There is a time limit after which there is no change, but again, there is no guarantee that I get a certain results and no way of assessing when something learned would not change with time.
Both to me seem reasonable but very annoying… I find it very hard to set up an objective function with so many unknowns..