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Tree based algorithms have the advantage that global or robust optimization of them is possible. Do your approaches offer similar guarantees?
by freemint 4y ago
Tree based algorithms have the advantage that global or robust optimization of them is possible. Do your approaches offer similar guarantees?
- ersiees 4y agoThe first work, I linked, arguably gets around this issue completely. There we train a neural network to approximate Bayesian prediction directly. It accepts the dataset as input. Thus, there is no optimisation procedure per dataset, just a forward pass. So far, this seems to be pretty stable.
- freemint 4y agoJust because you optimize network parameters to fit a surrogate model of the data doesn't mean you are not doing local optimization without guarantees on robustness or global optimality w.r.t. network parameters to fit the surrogate. Am i missing something?