in non metaphor terms: In many ML situations you can carry the train set with you test time. Eg: KNN, SVM, replay buffers, etc
this is one such case
--
the separate overfitting concern is fair, look at private holdout performance for that. it performs on par with TRM (a comparable model) in the private set, ofc with far less compute
in non metaphor terms: In many ML situations you can carry the train set with you test time. Eg: KNN, SVM, replay buffers, etc
this is one such case
--
the separate overfitting concern is fair, look at private holdout performance for that. it performs on par with TRM (a comparable model) in the private set, ofc with far less compute