… ral networks), we explore curriculum learning in various set-ups. … We hypothesize that
curriculum learning has both an effect … local minima obtained: curriculum learning can be seen as …

… imitates the meaningful learning order in … curriculum learning within a general CL framework,
elaborating on how to design a manually predefined curriculum or an automatic curriculum…

… link curriculum learning with the four main components of any machine learning approach: …
We observe that curriculum learning can be applied on each of these components, all these …

We introduce a method for automatically selecting the path, or syllabus, that a neural
network follows through a curriculum so as to maximise learning efficiency. A measure of the …

… They apply the automatic curriculum learning only to supervised sequence learning tasks,
while we consider also reinforcement learning tasks. They use the EXP3.S algorithm for …

… each task has a certain level of difficulty for learning the object class, which is defined by …
of a curriculum learning model over learning multiple tasks jointly and learning each task …

… curriculum learning or “student-driven” in selfpaced learning. … for curriculum learning and
self-paced learning, and revealed … as in curriculum learning, we assume the curriculum is total-…

… curriculum learning method, evaluation metrics, and the dimensions along which we will
classify curriculum learning … of the existing state of the art in curriculum learning in RL, with each …

… in terms of increased learning speed and … of curriculum learning, where we show how it
effectively modifies the optimization landscape. We then define the concept of an ideal curriculum…

… convergence of an ideal curriculum learning method is … curriculum learning in the context
of training a CNN. We describe a method which infers the curriculum by way of transfer learning …