It only considers the ranking orders of the instances for a specific target rather than their exact affinity values.
In LOR for a specific target, especial in the use of the pair-wise LOR, it transfers the compound affinity data to the pair-wise partially order pairs and treats these new order pairs as the instances.
Ranking loss is used to evaluate the average fraction of label pairs that are reversely ordered for the instance.
Ranking_Loss evaluates the average fraction of syndrome label pairs that are reversely ordered for the instance as follows: where z means denotes the complementary set of Y in Y.
That is, there are sentences of first-order arithmetic that can be deduced from the second-order induction axiom (together with the other axioms of arithmetic, which are common to first-order and second-order arithmetic) but not from the instances of the first-order induction schema (see Shapiro 1991: 110).
This eliminates the dependence of the results on the order in which instances are presented to the network, and also stabilizes the trajectories of the neurons.
Where Ω is a set of strings, ◯ σ∈Ω denotes the string obtained as the concatenation of all the strings in Ω lined up in lexicographic order (as a matter of fact, for the purpose of our reduction to work, the strings in Ω could be concatenated in any order, but we prefer to refer to a specific order so that the instance generated through the proposed reduction is uniquely defined).
In order to obtain the instance-specific information about bottleneck machine distribution, we first propose a new optimization model which relaxes some conventional constraints of the standard job shop problem.
The game presented the instances in order of increasing difficulty.
The second variant, SOGR-IB [ 38, 39] ("B" stands for "Batch update"), removes the dependence on the order in which instances are presented by only updating the weights after each cycle, where a cycle involves presenting the entire training set to the network, one instance at a time.
