1. P. H. Chen, C. J. Lin, and B. Schölkopf, A tutorial on ν-support vector machines, Appl. Stoch. Models. Bus. Ind. 2005, 21, 111-136. 2. A. J. Smola and B. Schölkopf, A tutorial on support vector regression, Stat. Comput. 2004, 14, 199-222. 5. K. R. Müller, S. Mika, G. Rätsch, K. Tsuda, and B. Schölkopf, An introduction to kernel-based learning algorithms, IEEE Trans. Neural Netw. 2001, 12, 181-201. 7. V. N. Vapnik, An overview of statistical learning theory, IEEE Trans. Neural Netw. 1999, 10, 988-999. 8. B. Schölkopf, S. Mika, C. J. C. Burges, P. Knirsch, K. R. Muller, G. Ratsch, and A. J. Smola, Input space versus feature space in kernel-based methods, IEEE Trans. Neural Netw. 1999, 10, 1000-1017. 9. C. J. C. Burges, A tutorial on Support Vector Machines for pattern recognition, Data Min. Knowl. Discov. 1998, 2, 121-167. 10. A. J. Smola and B. Schölkopf, On a kernel-based method for pattern recognition, regression, approximation, and operator inversion, Algorithmica 1998, 22, 211-231.

Google有名的关于云计算领域的三篇经典论文,及对应中文翻译文档，都集中在一起

An Analysis of Particle Swarm Optimizers.pdf Particle Swarm Optimization Based on Adaptive.pdf The fully informed particle swarm-simpler, maybe better.pdf The particle swarm - explosion, stability, and convergence in a multidimensional complex space.pdf

系统分析师四篇经典论文,有对应的点评！

acm常用算法，这是acm经典论文集。里面主要是2009年的国家集训队的acm培训资料。

这里有数十篇国内外的关于智能清洁机器人全覆盖路径规划的论文，而且有不少是发表在知名的杂志上的论文

推荐系统领域最经典的11片论文，具体的论文中文摘要欢迎参考我的博文，这些论文 可以说是推荐系统入门必看的经典之作，现在已经帮你整理好了。

包含了图像拼接几种经典算法的原版论文，还有其他非常经典的文献

非常经典的canny算法原文文献，很适合图像处理和边界提取

该资源包含了近些年经典的基于深度学习的目标检测论文，有RCNN、Fast-RCNN、Faster-RCNN、Mask-RCNN以及YOLO系列