Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Neural network based models have achieved impressive results on various specific tasks. Hover, in previous works, most models are learned separately based on single-task supervised objectives, which often suffer from insufficient training data. ,  propose two deep architectures which can be trained jointly on multiple related tasks. More specifically,  augment neural model with an external memory, which is shared by several tasks. Experiments on two groups of text classification tasks show that our proposed architectures can improve the performance of a task with the help of other related tasks.
['Pengfei Liu', 'Xipeng Qiu', 'Xuanjing Huang']
I am writing a research paper on a idea Deep Multi-Task Learning with Shared Memory
[{"from": "human", "value": "I am writing a research paper on a idea Deep Multi-Task Learning with Shared Memory"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Neural network based models have achieved impressive results on various specific tasks. Hover, in previous works, most models are learned separately based on single-task supervised objectives, which often suffer from insufficient training data. ,  propose two deep architectures which can be trained jointly on multiple related tasks. More specifically,  augment neural model with an external memory, which is shared by several tasks. Experiments on two groups of text classification tasks show that our proposed architectures can improve the performance of a task with the help of other related tasks."}]