总结说来，这些应用皆显示我们提出的成对特征学习演算法，可大幅增进分类准确率。
In summary, all these experiments demonstrate the improvement in accuracy by using the proposed paired feature learning in an AdaBoost classification framework.
本课程涵盖了语法、语意及对话处理模型，著重在机器学习或是以语料库为基础的方法及演算法。
It covers syntactic, semantic and discourse processing models, emphasizing machine learning or corpus-based methods and algorithms.
接著，我们利用这篇论文提出的成对特徵学习，开发出一套可直接在小波压缩域上进 行人脸侦测的新演算法。
Secondly, we develop a new face detection algorithm that works directly on the wavelet compressed domain based on the same paired feature learning framework.
本课程将介绍各领域中的机器学习使用者都应该知道的基础演算法、理论及实务工具。
The course teaches the most fundamental algorithmic, theoretical and practical tools that any user of machine learning needs to know.
本课程将介绍各领域中的机器学习使用者都应该知道的基础演算法、理论及实务工具。
The course teaches the most fundamental algorithmic, theoretical and practical tools that any user of machine learning needs to know.
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