椭球法在线学习Online Learning by Ellipsoid Method |
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课程网址: | http://videolectures.net/icml09_yang_olbem/ |
主讲教师: | Liu Yang |
开课单位: | 卡内基梅隆大学 |
开课时间: | 2009-08-26 |
课程语种: | 英语 |
中文简介: | 在这项工作中,我们扩展了椭球方法,该方法最初是为凸优化而设计的,用于在线学习。关键思想是通过椭球来近似与迄今为止收到的所有训练样例一致的分类假设。这与大多数在线学习算法形成对比,其中在每次迭代时仅维持单个分类器。在给出错误分类的示例的情况下,提出了用于更新椭球的质心和正定矩阵的有效算法。除了经典的椭圆体方法之外,还提出了用于在线学习的改进版本。导出两个椭球方法的错误边界。在将所提出的在线学习算法与两个最先进的在线学习者进行比较时,使用USPS数据集和三个UCI数据集的评估显示出令人鼓舞的结果。 |
课程简介: | In this work, we extend the ellipsoid method, which was originally designed for convex optimization, for online learning. The key idea is to approximate by an ellipsoid the classification hypotheses that are consistent with all the training examples received so far. This is in contrast to most online learning algorithms where only a single classifier is maintained at each iteration. Efficient algorithms are presented for updating both the centroid and the positive definite matrix of ellipsoid given a misclassified example. In addition to the classical ellipsoid method, an improved version for online learning is also presented. Mistake bounds for both ellipsoid methods are derived. Evaluation with the USPS dataset and three UCI data-sets shows encouraging results when comparing the proposed online learning algorithm to two state-of-the-art online learners. |
关 键 词: | 椭球方法; 凸优化; 在线学习 |
课程来源: | 视频讲座网 |
最后编审: | 2020-06-01:王勇彬(课程编辑志愿者) |
阅读次数: | 374 |