تقرير
Markov Random Walk Representations with Continuous Distributions
العنوان: | Markov Random Walk Representations with Continuous Distributions |
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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. |