Continual learning of context-dependent processing in neural networks
Continual learning of context-dependent processing in neural networks 摘要： 深度神經網絡能夠學習出輸入輸出之間的複雜的映射規則，但是這個規則是固定的，不能夠學習出多種場景下的不同的映射規則並根據場景的採用這些規則。正交權重修正以及場景以來的處理模塊能夠有效的解決深度神經網絡的這個限制使得深度神經網絡能夠適用於現實的多變場景
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相關文章
- 1. Exploring the teaching of deep learning in neural networks
- 2. An Overview of Multi-Task Learning in Deep Neural Networks
- 3. continual learning
- 4. Learning Structured Sparsity in Deep Neural Networks
- 5. Fundamentals of Deep Learning – Introduction to Recurrent Neural Networks
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- 7. Applications of Graph Neural Networks
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