Fully-adaptive Feature Sharing in Multi-Task Networks with Applications in Person Attribute Classification
CVPR, 2017.
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Abstract:
Multi-task learning aims to improve generalization performance of multiple prediction tasks by appropriately sharing relevant information across them. In the context of deep neural networks, this idea is often realized by hand-designed network architectures with layers that are shared across tasks and branches that encode task-specific fe...More
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