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. High-Dimensional Outlier Detection: The Subspace Method | Junting |
| Sep 25 | Ch 4. Proximity-based 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 | Query-Based Outlier Detection in Heterogeneous Information Networks (pdf) |
Hau |
| Apr 17 | Mining Query-Based Subnetwork Outliers in Heterogeneous Information Networks (pdf) |
Shebuti |
| Apr 10 | Community Distribution Outlier Detection in Heterogeneous Information Networks (pdf) |
Bryan |
| Apr 3 | Top-K Interesting Subgraph Discovery in Information Networks (pdf) |
Junting |
| Mar 27 | On Detecting Association-Based 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 Web-Scale Approach to Probabilistic Knowledge Fusion (pdf) | Vivek Kulkarni |
| Feb 20 | Object-Level Ranking: Bringing Order to Web Objects(pdf) | Vivek Pradhan |
| Feb 13 | Ranking-Based Clustering of Heterogeneous Information Networks with Star Network Schema(pdf) (slides) | Maryam |
| Feb 6 | PathSim: Meta Path-Based Top-K Similarity Search in Heterogeneous Information Networks (pdf) (slides) | Heeyoung |
| Jan 30 | Relational Retrieval Using a Combination of Path-Constrained Random Walks (pdf) | Leman |
| N/A | Ranking Methods for Networks (pdf) | Reading |
Tutorials
- 2015 Tutorial “Fraud Detection through Graph-Based User Behavior Modeling” ACM CCS, October 13, Denver, Colorado, US
- 2015 Tutorial “Graph-Based 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 4-8, Rome, Italy
- 2012 Tutorial “What is Strange in Large Networks? Graph-based Irregularity and Fraud Detection” IEEE ICDM, Dec 11-14, Brussels, Belgium
Courses
at CMU:
|
95-801 Data Mining Techniques | [www] |
|
95-869 Big Data and Large Scale Computing | [www] |
|
95-869 Big Data and Large Scale Computing | [www] |
|
95-828 Machine Learning for Problem Solving | [www] |
at Stony Brook:
|
CSE-590 Data Science Fundamentals | |
|
CSE-512 Machine Learning | |
|
CSE-590 Data Mining meets Graph Mining | |
|
CSE-512 Machine Learning | |
|
CSE-590 Networks and Data Mining Techniques | |
|
CSE-512 Machine Learning | |
|
CSE-590 Selected Topics in Data Mining and Networks |
