|
Statistical Learning (统计学习) |
Course Information |
This course is open to graduates and senior undergraduates in applied mathematics, statistics, and engineering who are involved in learning from data.
It covers some topics statistical learning, featured with several in-class projects in computational advertisement, bioinformatics, and social networks.
Prerequisite: linear algebra, basic probability and multivariate statistics, convex optimization; familarity with R and Matlab (better enhanced by C/++).
The Elements of Statistical Learning. 2nd Ed. By Hastie, Tibshirani, and Friedman
Jinzhu Jia and Yuan Yao
Thurday 6:40-9:30pm;
From the second week: 理教 309 (The first week in Rm 1114 Sci. Bldg 1st, Tuesday 2/26/2013)
2 hour lectures plus 1 hour discussion
Irregular assigned homeworks with projects, and a final major project. No final exam.
Chen, Xinyu (陈薪羽) Email: xycbaker (add "AT gmail DOT com" afterwards)
YAN, Bowei (闫博巍) Email: bwyan (add "AT pku DOT edu DOT cn" afterwards)
Date | Topic | Instructor | Scriber |
02/26/2013, Tue | Lecture 01: Introduction
| Y.Y. Dr. Xuehua Shen |
|
03/07/2013, Thu | Lecture 02: Overview on Supervised Learning [ Lecture 2 slides ]
| Y.Y. | |
03/14/2013, Thu | Lecture 03: Linear Models for Classification [ Lecture 3 slides ]
| Y.Y. | |
03/21/2013, Thu | Lecture 04: Linear Models for Regression [ Lecture 4 slides ]
| Y.Y. | |
03/28/2013, Thu | Lecture 05: Machine Learning in Sponsored Search and Online Advertisement
| Taifeng Wang, Jiang Bian, Tao Qin, Xuehua Shen |
|
04/11/2013, Thu |
Lecture 06: Basis Expansions and Regularization [ Lecture 6 slides ] [Homework] See the last slide in Lecture 6 slides . Due: April 25, 2013. [Readings] 1. Chapter 5, Elements of statistical learning. 2. Wahba, G. (1990). Spline Models for Observational Data, SIAM, Philadelphia. 3. Lin Y and Zhang H. (2006) Component selection and smoothing in smoothing splines of variance models. Annals of Statistics 34(5) 2272-2297. 4. Michal Aharon Michael Elad Alfred Bruckstein. K-SVD: DESIGN OF DICTIONARIES FOR SPARSE REPRESENTATION. 5. Julien Mairal, Francis Bach , Jean Ponce , Guillermo Sapiro, Andrew Zisserman (2008) Supervised Dictionary Learning |
Jinzhu Jia |
|
04/18/2013, Thu |
Continue with Lecture 06 Students give presentation on the home projects |
Jinzhu Jia |
|
04/25/2013, Thu |
Lecture 07: Basis Expansions and Regularization [ Lecture 7 slides ] [Homework] See the last slide in Lecture 7 slides . Due: May 9, 2013. [Readings] Chapter 6, Elements of statistical learning. |
Jinzhu Jia |
|
05/02/2013, Thu |
Lecture 08: Model Assessment and Selection [ Lecture 8 slides ] [Homework] See the last slide in Lecture 8 slides . Due: May 16, 2013. [Readings] Chapter 7, Elements of statistical learning. |
Jinzhu Jia |
|
05/09/2013, Thu |
Lecture 09: Model Inference and Averaging [ Lecture 9 slides ] [Homework] See the last slide in Lecture 9 slides . Due: May 23, 2013. [Readings] 1. Chapter 8, Elements of statistical learning. 2. Chapter 1, Computational Statistics. |
Jinzhu Jia |
|
05/16/2013, Thu |
Lecture 10: Model Inference and Averaging [ Lecture 9 slides ] [Homework] See the last slide in Lecture 9 slides . Due: May 30, 2013. [Project II] Due: May 30, 2013 [Readings] 1. Chapter 8, Elements of statistical learning. 2. Chapter 1, Computational Statistics. |
Jinzhu Jia Yuan Yao |
|
05/23/2013, Thu |
Lecture 11: Trees and Boosting [
Lecture 11 slides ] [Readings] 1. Chapter 9, Elements of statistical learning. 2. Chapter 10, Elements of statistical learning. 3. Friedman, J. H (1991). " Multivariate Adaptive Regression Splines" (with discussion). Annals of Statistics 19, 1. (software) 4. Friedman, J. H., Hastie, T. and Tibshirani, R. "Additive Logistic Regression: a Statistical View of Boosting." (Aug. 1998) 5. Y Freund,
RE Schapire (1997) A
decision-theoretic generalization of on-line learning and an application to
boosting. Journal of computer and system
sciences |
Jinzhu Jia |
|
05/30/2013, Thu | Lecture 12: Machine Learning from Computer Science and Boosting, by Prof. Liwei Wang
| Liwei Wang, Yuan Yao |
|
06/06/2013, Thu | Lecture 13: Final Projects [project_final.pdf]
| Yuan Yao; Xingqiang Wang et al. (CAS) |
|
06/13/2013, Thu | Lecture 14: Neural Networks and Deep Learning [project_final.pdf]
| Yuan Yao; Lei Jia (Baidu) |