I found Tanuj Yadav's answer to be interesting. Here's another way of solving it:
We have:
$$T(n)=\log_2{(n)}T(n/2)+1$$
I immediately sbustitute $n=2^m$, to get:
$$\begin{align}
T(2^m) &= \log_2{(2^m)}T(2^m/2)+1 \\
&= m T(2^{m-1}) + 1 \tag{4}
\end{align}$$
...and the above equation now seems very manageable. We get:
$$\begin{align}
T(2^m) &= 1 + (m + m(m-1) + m(m-1)(m-2) + \dots)\\
&= 1 + O(m!)
\end{align}$$
Substituting $m = \log_2{(n)}$, we have:
$$T(n) = O(\log_2{(n)}!)$$
which agrees with Tanuj Yadav's answer.
I note that we could have used both $m$ and $n$ to get, for (4):
$$T(n) = m T(n-1) + 1$$
This would give, for your question (1):
$$T(m) = n \left( T(m-1)^2 \right)$$
One more thing I can't resist mentioning... If you find recurrences as fascinating as I do, or are just curious, Herbert Wilf's GeneratingFunctionology, which you can find here is a very approachable introduction to all kinds of recurrences, and yet another take on them.