The convergence-rate conjecture for deep-limit minimisers
Let be minimisers of the finite-depth energies , and suppose the assumptions of the convergence theorem for and are satisfied. Let be a limit point of , and let be a subsequence converging to . With denoting the distance on the parameter space, the conjecture asserts that there exists such that
The convergence-rate conjecture. Under these assumptions, the distance between the convergent subsequence of finite-depth minimisers and its limit is . This conjectured rate is motivated by Taylor expansions of the recovery sequence, which suggest an rate for the minima when the relevant regularity is available, together with a local bound controlling parameter distance by the energy error. The result is not proved in the source.
References
Primary source
Matthew Thorpe and Yves van Gennip, “Deep Limits of Residual Neural Networks”, arXiv:1810.11741 (2022).
Progress summary
Nothing recorded yet. Refresh searches the literature and the public web for attempts on this problem, and writes the first summary here.
Solutions 0
No solutions have been posted yet.