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Recent studies highlight the potential for speed-ups in the optimization of engineering design parameters by conducting related designs jointly in a multi-task manner. [10] In machine learning , the transfer of optimized features across related data sets can enhance the efficiency of the training process as well as improve the generalization ...
Short title: Blended learning for quality higher education: selected case studies on implementation from Asia-Pacific; 2016; Author: Lim, Cher Ping; Wang Libing; UNESCO Office Bangkok and Regional Bureau for Education in Asia and the Pacific
In 2010, a scientific study found that a small percent of the population appeared to be much better at multitasking than others, and these people were subsequently labeled "supertaskers". [41] In 2015, another study supported the idea of supertaskers. This particular study showed that they tested people by making them drive on a driving ...
Multitasking can be defined as the attempt to perform two or more tasks simultaneously; however, research shows that when multitasking, people make more mistakes or perform their tasks more slowly. [33] Attention must be divided among all of the component tasks to perform them.
Multi-task learning (MTL) is a subfield of machine learning in which multiple learning tasks are solved at the same time, while exploiting commonalities and differences across tasks.
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Hal Pashler is Distinguished Professor of Psychology at University of California, San Diego.An experimental psychologist and cognitive scientist, Pashler is best known for his studies of human attentional limitations (his analysis of the Psychological refractory period effect concluded that the brain has discrete "processing bottlenecks" associated with specific types of cognitive operations).
A large review of studies on driving while media multitasking showed that using a hands-free phone while driving is just as dangerous as using a hand-held version, and that both can result in many different driving mistakes including missing stop signs, forgetting to reduce speed when necessary, and following too closely, among many others.