It is not clear whether the question uses the term Element as a synonym for Feature, but let's assume so.
In that case, the optimization of ten features, as opposed to optimization of three features, will converge more slowly.
If ... I start optimizing while having [three features] already solved with the almost the ground truth solution, will the optimization of the other [seven features] reach better or the same results, compared to [optimizing all ten together]?
The answers are maybe and no.
- The accuracy and reliability of the convergence toward ground truth (a formalized objective used to guide the optimization process) when split into groups of three and seven features may be better or worse than when left as a group of ten.
- Except in rare cases, the results will not be the same. The likelihood of identical results is so low it may never happen in the world in the next century except when conditions are arranged solely to cause it to occur.
Why then do may approaches group the dimensions of the result and converge on groups of axes, then another, then another, and back again to the first, iterating until the convergence goal is reached? This approach is used to reduce the time and computing resources used to reach the optimal. As the problem complexity increases, the use of groupings in this way is more common.