We prove that with high probability maximum sizes of induced forests in dense binomial random graphs are concentrated two consecutive values.

Scene-context plays an important role in scene analysis and object recognition. Among various sources of scene-context, we focus on scene-context scale, which means the effective scale of local context to classify an image pixel in a scene. This paper presents random forests based image categorization using the scene-context scale. The proposed method uses random forests, which are ensembles of...

Spatial linear mixed-models, consisting of a covariate effect and Gaussian process (GP) distributed spatial random effect, are widely used for analyses geospatial data. We consider the setting where is nonlinear. Random forests (RF) popular estimating nonlinear functions but applications RF data have often ignored correlation. show that this impacts performance adversely. propose RF-GLS, novel ...