DB004112-統計學習理論（全英文）

研究生課程開設申請表

開課院（系、所）：    beat365正版唯一   

課程申請開設類型： 新開√     重開□     更名□（請在□内打勾，下同）

一、課程介紹（含教學目标、教學要求等）（300字以内）

本課程涵蓋機器學習領域的基礎理論方面，包含監督學習的PAC模型，PAC可學性，過拟合，統一收斂性，奧卡姆剃刀，VC維數，Rademacher複雜度，性能增強，統計詢問方法和二進制傅立葉方法，隐私保護或通信約束下的學習算法複雜度等。希望通過本課程，同學可以對于機器學習算法的可學性和複雜度理論得到初步的認識，對于後續機器學習方面的科研起到幫助的作用。

二、教學大綱（含章節目錄）：（可附頁）

1. PAC模型和PAC 可學性

2. 過拟合問題和奧卡姆剃刀

3. 統一收斂性

4. VC理論和無限維問題的可學性

5. Radamacher 複雜度

6. 性能增強

7. 統計詢問和傅立葉方法

8. 隐私保護或通信約束下的學習算法

三、教學周曆

注：1.以上一、二、三項内容将作為中文教學大綱，在研究生院中文網頁上公布，四、五内容将保存在研究生院。2.開課學期為：春季、秋季或春秋季。3.授課語言為：漢語、英語或雙語教學。4.适用學科範圍為：公共，一級，二級，三級。5.實踐環節為：實驗、調研、研究報告等。6.教學方式為：講課、讨論、實驗等。7.學位課程考試必須是筆試。8.課件地址指在網絡上已經有的課程課件地址。9.主講教師簡介主要為基本信息（出生年月、性别、學曆學位、專業職稱等）、研究方向、教學與科研成果，以100至500字為宜。

四、主講教師簡介：

康維，1979年8月生，男，博士學曆，beat365正版唯一，信息與信号處理系教授。研究方向為信息論及其應用，信息安全和隐私保護，和統計學習理論。教學工作目前承擔本科生課程《數據安全與隐私保護》，博士生課程《網絡信息論》。科研方面多年來連續主持國家自然科學基金項目，發表高等級論文多篇。

五、任課教師信息（包括主講教師）：

六、課程開設審批意見

說明：1．研究生課程重開、更名申請也采用此表。表格下載：http:/seugs.seu.edu.cn/down/1.asp

2．此表一式三份，交研究生院、院（系）和自留各一份，同時提交電子文檔交研究生院。

Application Form For Opening Graduate Courses

School (Department/Institute)：School of Information Science and Engineering

Course Type: New Open √   Reopen □   Rename □（Please tick in □, the same below）

1. Course Introduction (including teaching goals and requirements) within 300 words:

We cover the basic theories of the area of machine learning, including PAC model for supervised learning, PAC learnability, overfitting, uniform convergence, Ocam’s razor, VC dimension, Rademacher complexity, boosting, statistical querya and binary fourier methods, learning complexity under privacy or communication constraints. Through this course, the students hopefully can obtain the basic understanding of the theories of the learnability and the complexity of machine learning and prepare for the future researches in the area of machine learning.

2. Teaching Syllabus (including the content of chapters and sections. A sheet can be attached):

1. PAC model and PAC learnability

2. Overfitting and Occam’s razor

3. Uniform convergence

4. VC theory and learnabitliy of infinite hypothesis space

5. Radamacher complexity

6. Boosting

7. Statistical query and fourier methods

8. Learning under privacy or communication constraints.

3. Teaching Schedule:

Note: 1.Above one, two, and three items are used as teaching Syllabus in Chinese and announced on the Chinese website of Graduate School. The four and five items are preserved in Graduate School.

 2. Course terms: Spring, Autumn , and Spring-Autumn term.   

 3. The teaching languages for courses: Chinese, English or Chinese-English.  

 4. Applicable range of discipline: public, first-class discipline, second-class discipline, and third-class discipline.  

 5. Practice includes: experiment, investigation, research report, etc.  

 6. Teaching methods: lecture, seminar, practice, etc.  

 7. Examination for degree courses must be in paper.  

 8. Teaching material websites are those which have already been announced.  

 9. Brief introduction of chief lecturer should include: personal information (date of birth, gender, degree achieved, professional title), research direction, teaching and research achievements. (within 100-500 words)  

4. Brief Introduction of Chief lecturer:

 Wei Kang, born in Aug. 1979, male,  PhD., Professor in Department of information and signal processing, School of information science and Engineering. Research areas include information theory and its applications, information security and privacy protection, and statistical learning theory. Current teaching includes undergraduate course <Data security and privacy protection> and Phd course <Network information theory>. Prof. Kang is the PI for multiple projects for Natural science foundation of China and has published multiple high-level journal papers.  

5. Lecturer Information (include chief lecturer)