Iterative Magnitude Pruning as a Renormalisation Group: A Study in The
  Context of The Lottery Ticket Hypothesis
Abu-Al Hassan
This thesis delves into the intricate world of Deep Neural Networks (DNNs),
focusing on the exciting concept of the Lottery Ticket Hypothesis (LTH). The
LTH posits that within extensive DNNs, smaller, trainable subnetworks termed
"winning tickets", can achieve performance comparable to the full model. A key
process in LTH, Iterative Magnitude Pruning (IMP), incrementally eliminates
minimal weights, emulating stepwise learning in DNNs. Once we identify these
winning tickets, we further investigate their "universality". In other words,
we check if a winning ticket that works well for one specific problem could
also work well for other, similar problems. We also bridge the divide between
the IMP and the Renormalisation Group (RG) theory in physics, promoting a more
rigorous understanding of IMP.