تقرير
Markov Random Walk Representations with Continuous Distributions
| العنوان: | Markov Random Walk Representations with Continuous Distributions |
|---|---|
| المؤلفون: | Yeang, Chen-Hsiang, Szummer, Martin |
| سنة النشر: | 2012 |
| المجموعة: | Computer Science Statistics |
| مصطلحات موضوعية: | Computer Science - Learning, Statistics - Machine Learning |
| الوصف: | Representations based on random walks can exploit discrete data distributions for clustering and classification. We extend such representations from discrete to continuous distributions. Transition probabilities are now calculated using a diffusion equation with a diffusion coefficient that inversely depends on the data density. We relate this diffusion equation to a path integral and derive the corresponding path probability measure. The framework is useful for incorporating continuous data densities and prior knowledge. Comment: Appears in Proceedings of the Nineteenth Conference on Uncertainty in Artificial Intelligence (UAI2003) |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/1212.2510 |
| رقم الأكسشن: | edsarx.1212.2510 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |