Slides: KDD2015 Tutorials

From the KDD website, here are most of the slides for the tutorials that occured during KDD 2015.

 

 

 

From  Big Data Analytics: Optimization and Randomization  by Tianbao Yang, Qihang Lin, Rong Jin

 
3-Hour Tutorials

• R1 (Tutorial 1) VC-Dimension and Rademacher Averages: From Statistical Learning Theory to Sampling Algorithms, Matteo Riondato, Eli Upfal  
• R2 (Tutorial 2) Graph-Based User Behavior Modeling: From Prediction to Fraud Detection, Alex Beutel Leman Akoglu Christos Faloutsos
• R3 (Tutorial 3) A New Look at the System, Algorithm and Theory Foundations of Large-Scale Distributed Machine Learning Eric Xing, Qirong Ho
• R4 (Tutorial 4) Dense subgraph discovery (DSD) , Aristides Gionis; Charalampos Tsourakakis
• R5 (Tutorial 5) Automatic Entity Recognition and Typing from Massive Text Corpora: A Phrase and Network Mining Approach ,  Xiang Ren, Ahmed El-Kishky, Chi Wang, Jiawei Han (code and more)
• R6 (Tutorial 6) Big Data Analytics: Optimization and Randomization Tianbao Yang, Qihang Lin, Rong Jin
• R7 (Tutorial 7) Big Data Analytics: Social Media Anomaly Detection: Challenges and Solutions, Sanjay Chawla, Yan Liu
• R8 (Tutorial 8) Diffusion in Social and Information Networks: Problems, Models and Machine Learning Methods , Manuel Gomez Rodriguez, Le Song
• R9 (Tutorial 9)Medical Mining (no slides) Myra Spiliopoulou, Pedro Pereira Rodrigues, Ernestina Menasalvas

1.5-Hour Tutorials

• S1 (Tutorial10) Large Scale Distributed Data Science using Apache Spark, James G. Shanahan, Liang Dai (example Python notebooks ...)
• S2 (Tutorial 11) Data-Driven Product Innovation, Xin Fu, Hernán Asorey
• S3 (Tutorial 12) Web Personalization and Recommender Systems, Shlomo Berkovsky, Jill Freyne  

 

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