Multitask learning in deep neural networks is an approach in which a single model is trained to perform multiple related tasks concurrently, exploiting commonalities and differences across tasks to ...

A team of researchers from the Skolkovo Institute of Science and Technology, the University of Vienna, and Sirius University of Science and Technology has published a study in the Journal of ...

Various studies have been conducted on multi-task learning techniques in natural language understanding (NLU), which build a model capable of processing multiple tasks and providing generalized ...

When a quantum computer processes data, it must translate it into understandable quantum data. Algorithms that carry out this 'quantum compilation' typically optimize one target at a time. However, a ...

Scientists have long said we can’t multitask. A new study says we can - ‘This is unlocking a whole new set of questions,’ one ...

Multi-target quantum compilation protocol. Its core is a quantum circuit designed for quantum computers. The circuit is built from a pool of gates, with the input being a set of target operations. It ...