First of all, we have to define the exact objective functional whose minimizers are paths of minimal length such that their signatures coincide with an assigned one. We formulate this task as an optimal control problem where the controls ai:=[x˙]i∈R,i∈{1,…,d} are the first ...
The evaluation metric for validation data is logloss, and early stopping was established after 50 rounds to avoid overtraining. We have checked that modifying slightly the XGBoost parameters does not change significantly our results. Furthermore, other ML algorithms suitable for the classification ...
In this study, 300 epochs were considered as the stopping criterion for the quasi Newton training method. At the higher level, which is called the supervising level, the PSO algorithm is used as a supervising optimization algorithm to find the optimal topology. At the supervising level, the ...
constraints will ensure the following three criteria to be enforced: (A)stopping Worm attacks 100% of the time,(B)enabling 100% protection for a given system without knowing any of the signatures of the individual Worms and (C)maintaining 100% effectiveness without periodic updates like virus ...
We will also not concern ourselves with systematic uncertainties in the model specification. Both of these issues will be addressed in part III. – The technique introduced in part I is directly applicable in searches where the signal parameters are known beforehand, e.g., rare Higgs signatures,...
To prove all the properties, we first assume that the adversary is an [Math Processing Error](ε1,ε2)-attacker, denoted by UnbEve (Unbounded Eve), and then will analyze how stopping UnbEve upon reaching a red query (i.e., converting it into Eve) will affect her execution. Remarks ...