Web Reference: Dec 7, 2015 · 深度学习论文中经常看到"sparse",所以应该是重要的概念,但一直不理解很困惑; 刚才在quora上的回答感觉很有帮助,尝试总结以下: sparse 代表数据为0,sparse数据的存在让不为0的dense数据聚集在一起; 因为存在数据聚集效应,所以才能学到特征和规律; 如果数据维度很高,噪音很多,原本为0的 ... Sparse Transformer 减轻计算量的方式通过让连接模式作用到 上,从而减轻 的复杂度。 如式 (3)。 对于第 个时间片的输入,首先使用 Key 和 Value 的权值矩阵乘以输入特征,得到 和 。 然后再将连接模式 作用到 和 上,得到稀疏的特征 和 。 通俗解释 Sparse Attention 的原理: 想象你在读一本长篇小说,如果每一页都要仔细读完全文才能理解剧情,效率会非常低。实际上,你会 快速跳过无关段落,只聚焦关键章节和人物对话,这就是 Sparse Attention(稀疏注意力) 的核心思想——让AI模型像人类一样“选择性关注重点,忽略次要信息 ...
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