课程号：MS206002

课程名：机器学习与计算视觉的现代优化方法

英文课程名：Modern Optimization Methods in Machine Learning and Computer Vision

开课单位：数学与统计学院

授课教师：Ismail Ben Ayed

责任教师：袁景   李碧

学分/学时：1学分/16学时

教师简介：Ismail Ben Ayed是魁北克大学的教授，医学图像与机器学习的首席教授。他的主要研究方向包括计算机视觉，机器学习，优化和医学图像分析。他已经出版了4部专著并且在期刊会议上分别发表90篇论文。他指导的学生已经超过20余名，包括硕士生，博士生，博士后。Ismail Ben Ayed is an Associate Professor in University of Quebec, and chair professor in medical imaging and machine learning. He works on Computer vision, machine learning, optimization and medical image analysis.He has published 4 books and 90 articles in journals and conferences. He has supervised more than 20 students, including MSc students, phd students and post-docs.

课程简介：本课程教学以国外优秀原版教材和最近三年发表文章作为主教材，结合当代优化方法在最新机器学习和计算视觉领域的应用进展，主要讲解5部分：1，机器学习与计算机视觉的数学模型简介，以及现代深度学习重大的计算方法；2，深度学习的典型数学模型；3，高阶正则化项的应用；4，无监督学习中的模型与优化；5，弱监督与半监督深度学习方法。This course combining  the international textbook and publications in lastest three years, introducing the progresses of the applications of the modern optimization methods in machine learning and computer vision, includes five parts: 1,  introduction to mathematical model of  computer vision and machine learning, and the computing methods of modern deep learning; 2,typical mathematical model of deep learning; 3, applicaltion s of regularization and high-order models; 4, unsupervised Learning: Models and optimization; 5, weakly and semi-supervised deep learning.

先修课程：机器学习初级课程