2007-EMNLP-CoNLL-Large-scale named entity disambiguation based on Wikipedia data

In this paper we present a method for fast surface reconstruction from large noisy datasets. Given an unorganized 3D point cloud, our algorithm recreates the underlying surface’s geometrical properties using data resampling and a robust triangulation algorithm in near realtime. For resulting smooth surfaces, the data is resampled with variable densities according to previously estimated surface curvatures. Incremental scans are easily incorporated into an existing surface mesh, by determining the respective overlapping area and reconstructing only the updated part of the surface mesh. The proposed framework is flexible enough to be integrated with additional point label information, where groups of points sharing the same label are clustered together and can be reconstructed separately, thus allowing fast updates via triangular mesh decoupling. To validate our approach, we present results obtained from laser scans acquired in both indoor and outdoor environments.

高等概率论，外国资深教授编写，很出名的一本书

只能说是大规模MIMO技术的经典书籍,只能说你不能错过

effective large scale stereo matching，用于快速立体匹配，代码量比较大，可以直接用在工程中。

Large Margin Rank Boundaries for Ordinal Regression

清晰 彩色 When most people hear “Machine Learning,” they picture a robot: a dependable butler or a deadly Terminator depending on who you ask. But Machine Learning is not just a futuristic fantasy, it’s already here. In fact, it has been around for decades in some specialized applications, such as Optical Character Recognition (OCR). But the first ML application that really became mainstream, improving the lives of hundreds of millions of people, took over the world back in the 1990s: it was the spam filter. Not exactly a self-aware Skynet, but it does technically qualify as Machine Learning (it has actually learned so well that you seldom need to flag an email as spam anymore). It was followed by hundreds of ML applications that now quietly power hundreds of products and features that you use regularly, from better recommendations to voice search.

来自于GOOGLE的mapreduce的开山之作，此文是原英文的中文版本，希望能互相参照，加深理解

It would be ludicrous to attempt to erect a 50 story oce building using the same materials and techniques a carpenter would use to build a single family home.

code for Large Scale Metric Learning from Equivalence Constraints