Slides of 10+ excellent tutorials at KDD 2015: Spark, graph mining and many more

August 17, 2015

(This article was first published on, and kindly contributed to R-bloggers)

by Yanchang Zhao

I attended the KDD 2015 conference in Sydney last week. At the conference, there were more than 10 tutorials and I went to two of them, which are 1) Graph-Based User Behavior Modeling: From Prediction to Fraud Detection, and 2) Large Scale Distributed Data Science using Apache Spark. Both tutorials were very popular and the rooms were full, with some audience standing and some sitting on the floor.

The speakers and the conference organizers kindly provided the tutorial slides online at I strongly suggest you to have a look at the slides, if you haven’t attended the conference. Below are a list of tutorials at the conference.

– VC-Dimension and Rademacher Averages: From Statistical Learning Theory to Sampling Algorithms
– Graph-Based User Behavior Modeling: From Prediction to Fraud Detection
– A New Look at the System, Algorithm and Theory Foundations of Large-Scale Distributed Machine Learning
– Dense subgraph discovery (DSD)
– Automatic Entity Recognition and Typing from Massive Text Corpora: A Phrase and Network Mining Approach
– Big Data Analytics: Optimization and Randomization
– Big Data Analytics: Social Media Anomaly Detection: Challenges and Solutions
– Diffusion in Social and Information Networks: Problems, Models and Machine Learning Methods
– Medical Mining
– Large Scale Distributed Data Science using Apache Spark
– Data-Driven Product Innovation
– Web Personalization and Recommender Systems

Another good news is, most (if not all) presentations at KDD 2015 have been video recorded, so hopefully the videos will be available at its website soon.

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