讲座题目：Conformal Predictors and Their Applications

主 讲 人：骆志远教授

讲座时间：2017年11月10日下午2:00

讲座地点：理学院钱伟长楼202报告厅

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讲座内容简介：

Several techniques such as Support Vector Machine (SVM) have been developed to tackle the problem of dimensionality by transferring the problem into high-dimensional space, and solving it in that space. They based on so-called kernel methods and can very often solve some high-dimensional problems. However, one drawback of these successful techniques is their lack of ability to provide rigorous confidence measures for the predictions they make. Recently a new set of techniques, called Conformal Predictors, have been developed that allows to make valid predictions and supply useful measures of confidence. The approach is based on recently developed approximations to the universal measures of confidence given by the algorithmic theory of randomness. The talk will describe the techniques and illustrate with some applications.

主讲人简介：

骆志远博士，伦敦大学皇家霍洛威学院计算机系教授，毕业于东南大学计算机科学系，并于英国爱丁堡赫瑞•瓦特大学获得计算机科学博士学位。目前主要从事数值分析和机器学习的研究及应用工作。骆志远博士已出版两部著作，发表论文90余篇，其中三篇论文获得“Best Paper”奖，获得过英国工程和物理科学研究委员会(EPSRC)、英国医学研究委员会(MRC)、英国皇家学会和欧盟第七框架计划以及地平线2020项目资助。