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
- 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
- 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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