… directly align the predictions between students and teachers. … in this study is to search for
an incremental learning method, … be maintained after repeating incremental training. And the …

… distillation as a prediction regularization technique for incremental learning. The high level …
predictions to the frozen model over a set of distillation images (while simultaneously learning …

… We show that performance is correlated with secondary class information (dark knowledge)
… With these lessons learned, class-incremental learning results on CIFAR-100 and ImageNet …

… pseudoinverse based on ridge regression, which greatly saves training consumption. We
introduce the incremental learning idea based on TCBLS in the online learning scenario …

… We propose to regularize the loss by enforcing the predictions to be less certain when
dealing with uncertain transferred knowledge by the use of maximum entropy regularizer (MER) (…

… This paper proposes a novel student academic performance prediction framework (ProbSAP)
that can efficiently extract more student characteristics from imbalanced datasets. …

… ’s necessary to update either an item’s or a learner’s trait vector, the TP of L-DTN or I-DTN is
reached and we need to incrementally learn … predicting effectiveness and training efficiency, …

… In this paper, we predict student performance and build a predictive model using Data
Mining Techniques. Firstly, we have collected the dataset after which, we have used Data pre…

… models to resist forgetting, and model rectification aims to reduce the biased prediction of
incremental learners. Template-based classification aims to transform inference into query-…

… This study also examines whether SLAT-Thinking adds in predicting academic performance
… that SLAT-Thinking will predict academic achievement and provide incremental validity over …