10-715 Advanced Introduction to Machine Learning - CMU - Fall 2015

The rapid improvement of sensory techniques and processor speed, and the availability of inexpensive massive digital storage, have led to a growing demand for systems that can automatically comprehend and mine massive and complex data from diverse sources. Machine Learning is becoming the primary mechanism by which information is extracted from Big Data, and a primary pillar that Artificial Intelligence is built upon. This course is designed for Ph.D. students whose primary field of study is machine learning, or who intend to make machine learning methodological research a main focus of their thesis. It will give students a thorough grounding in the algorithms, mathematics, theories, and insights needed to do in-depth research and applications in machine learning. The topics of this course will in part parallel those covered in the general graduate machine learning course (10-701), but with a greater emphasis on depth in theory and algorithms. The course will also include additional ad

感测技术的迅速进步、处理器速度的提升以及廉价的大容量数字存储的普及，共同催生了对于能够自动从多元化数据源中理解和挖掘海量且复杂数据的系统日益增长的需求。机器学习正逐渐成为从大数据中提取信息的主要机制，并成为构建人工智能的基石。本课程专为以机器学习为主要研究领域或计划将机器学习方法论研究作为其论文主要焦点的博士研究生设计。课程将为学生提供深入研究和应用机器学习所需的算法、数学、理论与洞见的全面基础。本课程的内容部分将与普通研究生机器学习课程（10-701）所涵盖的主题相呼应，但更侧重于理论及算法的深度。此外，课程还将包含额外的...