The phrase "auxiliary learning" is correct and usable in written English.
It can be used in contexts related to education, training, or supplementary learning methods that support primary learning processes.
Example: "The program focuses on auxiliary learning techniques to enhance students' understanding of complex subjects."
Alternatives: "supplementary learning" or "supportive learning".
Recently, transfer learning [7] has become a popular machine learning method which utilizes auxiliary data for learning.
The first method, prediction propagation, propagates highly confident predictions of one local model to another as the auxiliary examples, thus learning from information-rich regions of the training network to help predict the information-poor regions.
Our approach compensates for model error by learning an auxiliary dynamical model for the unknown parameters.
Plans to axe classroom assistants posts and replace them with a lower number of new learning support auxiliaries were scaled back earlier this month.
Finally, functions of the system was divided into four modules from double angles of teaching staff and trainees respectively, including auxiliary self-learning, human-computer interaction, arrangements for training task, training effect feedback and evaluation.
Finally, an important auxiliary issue is: How can students' learning be recorded as it unfolds?
The Achieve Program at Southern Illinois University offers A.D.D. coaching as part of its auxiliary program for students with A.D.D. or learning disabilities.
Many researchers have proposed all kinds of methods to transfer learning information or knowledge from auxiliary data.
Both nurses and auxiliary nurses indicate that there is a learning effect from PA.
Therefore, we propose to model them using a multi-task (sequence-to-sequence?) learning framework where these (and other, auxiliary) tasks can benefit from shared representations.
When one considers these issues in operational terms, it becomes clear that RPE is an auxiliary variable associated with stochastic approximation schemes for learning value functions.
