… We flexibly allow the model to predict either an old class or the background on any region
not associated with an annotation on the classification loss to alleviate catastrophic forgetting. …

… (FSCIL)presents an extension of the Class Incremental Learning (CIL)problem where a …
, where a prediction network is trained to predict prototypes. The predicted prototypes and the …

… Here, we propose a novel incremental learning approach which combines a deep …
incremental learning designed to operate online with stream data. During its operation, predictions …

… For example, ElGamal et al. predict students’ programming performance based on their …
only reflect a student’s background, and not their effort in the course, and their predictions may …

… during training, which is susceptible to privacy concerns. This paper proposes an incremental
learning … where P is the binary prediction of the student model and G is the ground truth. In …

… Lifelong learning has attracted much attention, but existing works still struggle to … of incremental
learning. In this work, we propose PODNet, a model inspired by representation learning. …

… Notice that Deep Learning (DL) can provide high-quality … DL for early prediction of students’
performance using data … a total of 2058 students during 6 semesters (longitudinal study). We …

… student performance prediction model to help with the early identification of at-risk students
… This will enable instructors to apply educational interventions to prevent students from failing…

… They are interested in prediction accuracy but pay less attention to interpretability. … predict
and analyze student performance in academic competition. In this model, student performance …

… Therefore, this study aims to examine the incremental value … (non-cognitive) in predicting
students’ early academic … after controlling for gender, age and prior education. To this end, an …