2012 Dragon Star Lectures (Link)

Part I: Classification (Qiang Yang)

Introduction to Machine Learning (ML) by Ethem Alpaydin. Website: http://www.cmpe.boun.edu.tr/~Eethem/i2ml2e/
"统计学习方法”，李航。清华大学出版社
Data Mining (TSK): Tan, Steinbach, Kumar Book： http://www-users.cs.umn.edu/~kumar/dmbook/index.php
Data Mining (DM) by J. Han, M. Kamber and J. Pei: http://www.cs.uiuc.edu/~hanj/bk3/

Lecture	Slides	Reading Material
Part I: General Introduction (May 21, 2012)
Introduction	slides	KDD Cup Intro Origin of 'Data Mining?' (link) KDD in China (pages 72-102)
Decision Trees	slides	DM, Chapters 8, 9; TSK: Chapter 4.
Neural Networks	slides	DM, Chapters 8, 9; TSK: Chapter 4.
Bayesian Classifiers	slides	DM, Chapters 8, 9; TSK: Chapter 4.
Support Vector Machines	slides	DM, Chapters 8, 9; TSK: Chapter 4.
Ensemble Classifiers	slides	TSK: Chapter 5.
Theoretical Issues	slides	ML: Chapter 2.
Collaborative Filtering	slides	ACM TIST Special Issue on Social Rec Systems
Text and Web Mining	slides	Intro to IR, Ullman's book
Part II: Transfer Learning (May 22, 2012)
Introduction	Introduction	Transfer Learning Survey
Inductive Transfer Learning	Inductive Transfer Learning Slides	References
Heterogeneous Transfer Learning and	HTL Slides	References Heterogeneous Transfer Learning (ACL Talk)
Transfer Learning in Social Networks and Recommender Systems	TL Link Talk	References ICML Paper
Transfer Learning Applications	Applications	2009 Ubicimp Paper
Adaptive Transfer Learning and Collaborative Recommendation (Presented by Cao Bin, MSRA)	Adaptive Transfer Learning	AAAI 2010 Paper, ICML 2010 Paper
Graph-based Transfer Learning	Eigen-Transfer Slides	Eigen Transfer
Source-free Transfer Learning	Source-Selection Free Transfer Learning	IJCAI Paper on SSFTL
Theoretical Results		Blitzer's Paper