Decision Forests for Classification, Regression, Density Estimation, Manifold Learning and Semi-Supervised Learning

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Apparel Classification with Style (2012, background): “Therefore, previous work also studied the extension of RFs to semi-supervised learning [19, 5] in order to benefit from additional unlabeled data, which is usually cheap to collect.”
Learning a No-Reference Quality Metric for Single-Image Super-Resolution (2016, methodology): “We refer readers to [39] for more details about regression forest.”
Random Forests (2012, unknown): “また, 冒頭にあげたインターネット上の参考資料 [2], [6], [8], [20] がなければ本稿をまとめることはできなかった.”
Random Forests for Real Time 3D Face Analysis (2012, background): “A detailed introduction to decision forests and their applications in computer vision can be found in Criminisi et al. (2011).”
The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS) (2015, methodology): “We use a decision forest as a classifier [89], which has the advantage of being able to handle multi-class problems and providing a probabilistic output [89].”