論文-《Towards Optimal Binary Code Learning via Ordinal Embedding》
Introduction 以前的哈希算法僅僅利用原始空間數據的相似度信息，本文的算法嘗試將原始空間的排序關係映射到的低緯度的漢明空間中； approach constructs a directed, unweighted ordinal graph to capture the original relation among data points, upon which we learn
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相關文章
- 1. 論文閱讀理解 - Deep Metric Learning via Lifted Structured Feature Embedding
- 2. 論文閱讀：Deep Metric Learning via Lifted Structured Feature Embedding
- 3. 論文解析：NASE: Learning Knowledge Graph Embedding for Link Prediction via Neural Architecture Search
- 4. 【論文解讀 WSDM 2018 | DRL】Curriculum Learning for Heterogeneous Star Network Embedding via DRL
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- 9. 論文閱讀：Collaborative Deep Embedding Via Dual Networks
- 10. 通過離散局部線性嵌入實現最優流形散列 -Toward Optimal Manifold Hashing via Discrete Locally Linear Embedding