Continual learning of context-dependent processing in neural networks
Continual learning of context-dependent processing in neural networks 摘要： 深度神经网络能够学习出输入输出之间的复杂的映射规则，但是这个规则是固定的，不能够学习出多种场景下的不同的映射规则并根据场景的采用这些规则。正交权重修正以及场景以来的处理模块能够有效的解决深度神经网络的这个限制使得深度神经网络能够适用于现实的多变场景
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相关文章
- 1. Exploring the teaching of deep learning in neural networks
- 2. An Overview of Multi-Task Learning in Deep Neural Networks
- 3. continual learning
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- 5. Fundamentals of Deep Learning – Introduction to Recurrent Neural Networks
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- 7. Applications of Graph Neural Networks
- 8. Neural Networks: Learning: Backpropagation intuition
- 9. Neural Networks: Learning: Random initialization
- 10. Neural Networks and Deep Learning -- Class 3: Shallow neural networks