将数位资料特征化，并从中识别感兴趣的特征和模式的基本概念。信号理解问题的基本工具和理论，及其在用户模型，情感识别，语音识别与理解，计算机视觉，生理分析等方面的应用。决策理论，统计分类，最大似然和贝叶斯估计，非参数方法，非监督的学习与聚类。补充课题中会涉及人机学习领域中当前活跃的研究内容。

Fundamentals of characterizing and recognizing patterns and features of interest in numerical data. Basic tools and theory for signal understanding problems with applications to user modeling, affect recognition, speech recognition and understanding, computer vision, physiological analysis, and more. Decision theory, statistical classification, maximum likelihood and Bayesian estimation, non-parametric methods, unsupervised learning and clustering. Additional topics on machine and human learning from active research.