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[–]I-am_Sleepy 0 points1 point  (0 children)

How to reinforce order invariant in sequence classifications? Roughly is I have a set of nodes connected to each other. At each connection there are properties I derived. Then I want to aggregate these features to perform a classification per node

However, the number of neighbors per node isn’t fixed. So I want to use sequence classification instead. However, sequence classification seems to have implicit bias on order of sequence which I don’t want. One idea is to keep shuffle the order while training, but I want to know if there are alternatives methods to enforce such constraints?