Writer: Yongshin Kim
Definition
- Single task
- $input\;X \rightarrow output \;Y$
- Multi task
- $input\;X\rightarrow output\;Y_1,\;Y_2,\;Y_3 \;...$
- ex) Object detection: detection(classification) + location(regression)
- ex) Korean $\rightarrow$ Chinese, English, Japanese
- Korean $\rightarrow$ Chinese, Korean $\rightarrow$ English, Korean $\rightarrow$ Japanese
Advantage
- Knowledge transfer
- Useful information from learning $Y_1$ is delivered to other $Y_2$ and $Y_3$.
- Prevent overfitting
- Learning a more generalized representation to fit multiple tasks simultaneously.
- Computational efficiency
- Real-world application
Disadvantage
- Negative transfer
- $Y$ may exist that adversely affects other tasks.
- Task unbalancing
- If the learning difficulty varies greatly from task to task, the robustness of the model decreases.