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About Robust Continuous Clustering: Sohil Atul Shah and Vladlen Koltun
The document presents a new clustering algorithm called robust continuous clustering (RCC). Key points: 1) RCC optimizes a smooth continuous objective function to cluster data, allowing clustering to be integrated into end-to-end machine learning pipelines. 2) It can untangle heavily mixed clusters using robust estimators. Optimization is done with standard linear solvers. 3) The algorithm is evaluated on large image, text, sensor, and biological datasets, significantly outperforming prior methods on average. 4) It can be extended to perform joint clustering and dimensionality reduction (RCC-DR) by optimizing a global objective to learn embeddings and clusters simultaneously.
Detailed Information
| Author: | ['jayjay'] |
|---|---|
| Publication Year: | 2019 |
| Pages: | 6 |
| Language: | English |
| Format: | |
| Price: | FREE |
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