Reading Seminar
Date  Title  Speaker 
Fall 2015  Outlier Analysis. Book by Charu Aggarwal.  
Nov 27  Ch 12. Applications of Outlier Analysis  Leman 
Nov 20  Ch 11. Outlier Detection in Graphs and Networks  Shebuti 
Nov 13  Ch 10. Spatial Outlier Detection  Aria 
Nov 6  Ch 9. Outlier Detection in Discrete Sequences  Brian 
Oct 30  Outlier Ensemble Techniques  Leman 
Oct 23  Ch 8. Time Series and Multidimensional Streaming Outlier Detection  Ali 
Oct 16  Ch 7. Outlier Detection in Categorical, Text and Mixed Attribute Data  Santhosh 
Oct 9  Ch 6. Supervised Outlier Detection  Abhinav 
Oct 2  Ch 5. HighDimensional Outlier Detection: The Subspace Method  Junting 
Sep 25  Ch 4. Proximitybased Outlier Detection  Darius 
Sep 18  Ch 3. Linear Models for Outlier Detection  Emaad 
Sep 11  Ch 2. Probabilistic and Statistical Models for Outlier Detection  Conor 
Sep 4  Ch 1. An Introduction to Outlier Analysis  Leman 
Spring 2015  Heterogeneous Graph Mining. See here for intro/overview.  
May 8  QueryBased Outlier Detection in Heterogeneous Information Networks (pdf) 
Hau 
Apr 17  Mining QueryBased Subnetwork Outliers in Heterogeneous Information Networks (pdf) 
Shebuti 
Apr 10  Community Distribution Outlier Detection in Heterogeneous Information Networks (pdf) 
Bryan 
Apr 3  TopK Interesting Subgraph Discovery in Information Networks (pdf) 
Junting 
Mar 27  On Detecting AssociationBased Clique Outliers in Heterogeneous Information Networks (pdf) 
Abhinav 
Mar 13  Personalized Entity Recommendation: A Heterogeneous Information Network Approach (pdf)  Mohammad 
Mar 6  Trust, but Verify: Predicting Contribution Quality for Knowledge Base Construction and Curation (pdf)  Santhosh 
Feb 27  Knowledge Vault: A WebScale Approach to Probabilistic Knowledge Fusion (pdf)  Vivek Kulkarni 
Feb 20  ObjectLevel Ranking: Bringing Order to Web Objects(pdf)  Vivek Pradhan 
Feb 13  RankingBased Clustering of Heterogeneous Information Networks with Star Network Schema(pdf) (slides)  Maryam 
Feb 6  PathSim: Meta PathBased TopK Similarity Search in Heterogeneous Information Networks (pdf) (slides)  Heeyoung 
Jan 30  Relational Retrieval Using a Combination of PathConstrained Random Walks (pdf)  Leman 
N/A  Ranking Methods for Networks (pdf)  Reading 
Tutorials
 2015 Tutorial “Fraud Detection through GraphBased User Behavior Modeling” ACM CCS, October 13, Denver, Colorado, US
 2015 Tutorial “GraphBased User Behavior Modeling: From Prediction to Fraud Detection” ACM KDD, August 10, Sydney, AU
 2014 Tutorial “Big Graph Mining for the Web and Social Media” ACM WSDM, February, NYC, USA
 2013 Tutorial “Big Graph Mining: Algorithms, Anomaly Detection, and Applications” IEEE/ACM ASONAM, August, Niagara Falls, Canada
 2013 Tutorial “Anomaly, Event, and Fraud Detection in Large Graph Datasets” ACM WSDM, Feb 48, Rome, Italy
 2012 Tutorial “What is Strange in Large Networks? Graphbased Irregularity and Fraud Detection” IEEE ICDM, Dec 1114, Brussels, Belgium
Courses
at CMU:

95801 Data Mining Techniques  [www] 

95869 Big Data and Large Scale Computing  [www] 

95869 Big Data and Large Scale Computing  [www] 

95828 Machine Learning for Problem Solving  [www] 
at Stony Brook:

CSE590 Data Science Fundamentals  

CSE512 Machine Learning  

CSE590 Data Mining meets Graph Mining  

CSE512 Machine Learning  

CSE590 Networks and Data Mining Techniques  

CSE512 Machine Learning  

CSE590 Selected Topics in Data Mining and Networks 