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
Apr 17 Mining Query-Based Subnetwork Outliers in
Heterogeneous Information Networks
Apr 10 Community Distribution Outlier Detection in
Heterogeneous Information Networks
Apr 3 Top-K Interesting Subgraph Discovery in
Information Networks (pdf)
Mar 27 On Detecting Association-Based Clique Outliers in
Heterogeneous Information Networks (pdf)
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




at CMU:


  • Fall A2 2017
95-801 Data Mining Techniques [www]
  • Fall A2 2017
95-869 Big Data and Large Scale Computing [www]
  • Spring A4 2017
95-869 Big Data and Large Scale Computing [www]
  • Spring 2017
95-828 Machine Learning for Problem Solving [www]
at Stony Brook:
  • Fall 2015
CSE-590 Data Science Fundamentals
  • Spring 2015
CSE-512 Machine Learning
  • Fall 2014
CSE-590 Data Mining meets Graph Mining
  • Spring 2014
CSE-512 Machine Learning
  • Fall 2013
CSE-590 Networks and Data Mining Techniques
  • Spring 2013
CSE-512 Machine Learning
  • Fall 2012
CSE-590 Selected Topics in Data Mining and Networks