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Related Questions
- What are the key factors to consider when selecting tasks for multi-task learning to ensure diversity and prevent task redundancy?
- How can we use clustering algorithms to group tasks and identify diverse subsets for multi-task learning?
- What is the role of task similarity metrics, such as cosine similarity or Jaccard similarity, in selecting diverse tasks for multi-task learning?
- Can you explain the concept of task interleaving and how it can be used to create diverse task sets for multi-task learning?
- How do we balance the trade-off between task diversity and task similarity in multi-task learning to achieve optimal performance?
- What are some common techniques for evaluating the diversity of task sets in multi-task learning, such as entropy or mutual information?
- How can we use prior knowledge or domain expertise to guide the selection of diverse tasks for multi-task learning in specific domains?
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