Machine Learning: Discriminative and Generativeis designed for an audience composed of researchers & practitioners in industry and academia. The book is also suitable as a secondary text for graduate-level students in computer science and engineering. ...
The books in this innovative series collect papers written in the context of successful competitions in machine learning. They also include analyses of the challenges, tutorial material, dataset descriptions, and pointers to data and software. Together with the websites of the challenge competitions, ...
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Christopher M. Bishop Pattern Recognition and Machine Learning springer点赞(0) 踩踩(0) 反馈 所需:1 积分 电信网络下载 ok272733314 2014-06-09 09:57:59 评论 还不错唉,说明的很详细的说~~~liucm1005 2013-10-11 22:34:32 评论 很好的教材。
Linear Algebra and Optimization for Machine LearningCharu C. AggarwalA Textbook
[Studies in Computational Intelligence] Multi-Objective Machine Learning Volume 16 || Multi-Objective Optimization of Support Vector Machines Jin,Yaochu 被引量: 0发表: 2006年 Multi-Objective Neural Network Optimization for Visual Object Detection In: Jin, Y. (Ed.), Multi-Objective Machine Learning,...
particular task. Computational Intelligence (CI) approaches are alternative solutions to for automatic computer vision and image processing systems; they include the use of tools as machine learning and soft computing. Researchers from all over the world are working hard creating new algorithms that ...
As more of such structured and semi-structured data is becoming available, the machine learning methods that can leverage the signal in these data are becoming more valuable, and the importance of being able to effectively mine and learn from such data is growing. These graphs are typically ...
Bishop: Pattern Recognition and Machine Learning. Cowell, Dawid, Lauritzen, and Spiegelhalter: Probabilistic Networks andExpert Systems. Doucet, de Freitas, and Gordon: Sequential Monte Carlo Methods in Practice. Fine: Feedforward Neural Network Methodology. Hawkins and Olwell: Cumulative Sum Charts and...
LCBuADAaML 2021 : WordCIST 2021 (Springer) 1st Workshop on Leveraging customer behavior using advanced data analytics and Machine learning techniques