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Soft learning probabilistic circuits
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DOI：10.1016/j.ijar.2025.109467.png)
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Abstract
En 中文
• We address the problem of learning a probabilistic circuit from data; we consider the well-known LearnSPN algorithm. • We show that LearnSPN's hard clustering may hinder generalization, and propose using soft clustering to improve it. • We demonstrate through various experiments that our solution can lead to improved performance.
Keywords:
Probabilistic circuits
Probabilistic inference
Probabilistic graphical models
Missing data
Journal
IF:
3
Papers:
2.9K
Citations:
5.1K
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