ViBR: Visualizing Bipartite Relations at Scale with the Minimum Description Length Principle
论文传送门 作者 纽约大学： Gromit Yeuk-Yin 博世北美研究中心 Panpan Xu Zeng Dai Liu Ren 摘要： 二部图模拟了许多真实世界中大规模的关键关系，比如顾客购买商品，立法者投票、人与不同社会群体的联系，车辆发生故障等等。然而，对具有成千上万甚至更多节点或边的二部图进行可视化是非常有挑战的。在本文中，我们提出了一种基于最小描述长度（MDL）的新的视觉摘要技术。该
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相关文章
- 1. some understanding of《Inferring Decision Trees Using the Minimum Description Length Principle*》
- 2. Learning with Privacy at Scale
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- 4. Running Kafka At Scale
- 5. Winglets: Visualizing Association with Uncertainty in Multi-class Scatterplots
- 6. THE GOLDILOCKS PRINCIPLE: READING CHILDREN’S BOOKS WITH EXPLICIT
- 7. Dealing with Scale in AR
- 8. The Maximum Entropy Principle
- 9. The MegaFace Benchmark-1 Million Faces for Recognition at Scale
- 10. Visualizing an Assassin Puzzle