题目：Review of Modeling Techniques for Classification and Regression with Applications in Medicine and Engineering

主讲人：Prof. Uwe Kruger (Rensselaer Polytechnic Institute, U.S.)

时间：7月15日下午14:30-18:00

地点：工控老楼414室

摘要：This sequence of seminar talks introduces various multivariate linear and nonlinear modeling methods for classification and regression tasks. Particular focus is placed upon reviewing data structures, modeling methods, identification of parameterized models and how to independently verify the performance of identified models. To demonstrate how to apply these methods and how to interpret the information that can be obtained from identified models, the talks cover various application studies to medical and engineering applications. A tentative breakdown of the individual lectures is as follows:

A. Linear Methods: 1) Classification methods; 2) Modeling methods including PCA, OLS, CCR, MR, PLS, discussion of dynamic data structures

B. Nonlinear Methods: 1) Introduction to kernel methods; 2) Application of kernel methods for classification and regression modeling including considerations of dynamic data structures

C. General Framework for Data Models and Model Validation: 1) Introduction of a Framework for Data Models in Classification and Modeling Applications; 2) Aim of validation and statistical independence, concept of cross validation

D. Medical and engineering application studies

主讲人简介：Dr. Uwe Kruger is the professor of Practice, Department of Biomedical Engineering, Rensselaer Polytechnic Institute, Troy NY, U.S.. His researches include developing methods for applications of probability and statistics engineering mathematics, signal processing, data chemometrics, system identification and modeling.  He has published over 50 journal articles，5 book chapters and 1 book (published by John Wiley & Sons), which  totally have attracted more than 1600 citations, (Scopus, Web of Science, Google Scholar), an h-index of 22. He also has collaborated with some famous industrial companies and produced 2 patents attracting 26 citations in  Google Scholar.

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