《Multinomial Distribution Learning for Effective Neural Architecture Search》

時間 2021-01-02

標籤論文閱讀記錄简体版

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Contributions: 1、 propose a Multinomial Distribution Learning for extremely effective NAS, which considers the search space as a joint multinomial distribution. 2、Propose a performance ranking hypothe

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1. Research Guide for Neural Architecture Search
2. NEURAL ARCHITECTURE SEARCH WITH REINFORCEMENT LEARNING
3. Neural architecture search
4. Neural Architecture Search — Limitations and Extensions
5. 《Neural Architecture Search with Reinforcement Learning》翻譯
6. Neural Architecture Search(NAS)
7. 論文筆記——NEURAL ARCHITECTURE SEARCH WITH REINFORCEMENT LEARNING
8. 論文筆記《Neural Architecture Search With Reinforcement Learning》
9. Neural Architecture Search with Reinforcement Learning論文總結
10. 論文解析：NASE: Learning Knowledge Graph Embedding for Link Prediction via Neural Architecture Search
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1. Research Guide for Neural Architecture Search
2. NEURAL ARCHITECTURE SEARCH WITH REINFORCEMENT LEARNING
3. Neural architecture search
4. Neural Architecture Search — Limitations and Extensions
5. 《Neural Architecture Search with Reinforcement Learning》翻譯
6. Neural Architecture Search(NAS)
7. 論文筆記——NEURAL ARCHITECTURE SEARCH WITH REINFORCEMENT LEARNING
8. 論文筆記《Neural Architecture Search With Reinforcement Learning》
9. Neural Architecture Search with Reinforcement Learning論文總結
10. 論文解析：NASE: Learning Knowledge Graph Embedding for Link Prediction via Neural Architecture Search

>>更多相關文章<<