Graph Clustering

• Non-exhaustive, Overlapping Clustering (pdf, software)
  J. Whang, Y. Hou, D. Gleich, I. Dhillon.
  IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI) 41(11), pp. 2644–2659, August 2018.
• Fast Multiplier Methods to Optimize Non-exhaustive, Overlapping Clustering (pdf)
  Y. Hou, J. Whang, D. Gleich, I. Dhillon.
  In SIAM International Conference on Data Mining (SDM), pp. 297–305, May 2016. (Oral)
• Overlapping Community Detection Using Neighborhood-Inflated Seed Expansion (pdf)
  J. Whang, D. Gleich, I. Dhillon.
  IEEE Transactions on Knowledge and Data Engineering (TKDE) 28(5), pp. 1272–1284, 2016.
• Non-exhaustive, Overlapping Clustering via Low-Rank Semidefinite Programming (pdf, slides)
  Y. Hou, J. Whang, D. Gleich, I. Dhillon.
  In ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), pp. 427–436, August 2015. (Oral)
• Scalable Data-driven PageRank: Algorithms, System Issues, and Lessons Learned (pdf)
  J. Whang, A. Lenharth, I. Dhillon, K. Pingali.
  In International European Conference on Parallel and Distributed Computing (Euro-Par), pp. 438–450, August 2015. (Oral)
• Non-exhaustive, Overlapping k-means (pdf, software)
  J. Whang, I. Dhillon, D. Gleich.
  In SIAM International Conference on Data Mining (SDM), pp. 936–944, May 2015.
• Prediction and Clustering in Signed Networks: A Local to Global Perspective (pdf)
  K. Chiang, C. Hsieh, N. Natarajan, A. Tewari, I. Dhillon.
  Journal of Machine Learning Research (JMLR) 15, pp. 1177-1213, March 2014.
• Stochastic Blockmodel with Cluster Overlap, Relevance Selection, and Similarity-Based Smoothing (pdf, slides)
  J. Whang, P. Rai, I. Dhillon.
  In IEEE International Conference on Data Mining (ICDM), pp. 817 – 826, December 2013. (Oral)
• Overlapping Community Detection Using Seed Set Expansion (pdf, slides)
  J. Whang, D. Gleich, I. Dhillon.
  In ACM Conference on Information and Knowledge Management (CIKM), pp. 2099-2108, October 2013. (Oral)
• Scalable and Memory-Efficient Clustering of Large-Scale Social Networks (pdf, slides)
  J. Whang, X. Sui, I. Dhillon.
  In IEEE International Conference on Data Mining (ICDM), pp. 705-714, December 2012. (Oral)
• Scalable Clustering of Signed Networks using Balance Normalized Cut (pdf, slides)
  K. Chiang, J. Whang, I. Dhillon.
  In ACM Conference on Information and Knowledge Management (CIKM), pp. 615-624, October 2012. (Oral)
• Clustering with Multiple Graphs (pdf)
  W. Tang, Z. Lu, I. Dhillon.
  In IEEE International Conference on Data Mining (ICDM), December 2009.
• Semi-Supervised Graph Clustering: A Kernel Approach (pdf)
  B. Kulis, S. Basu, I. Dhillon, R. Mooney.
  Machine Learning 74(1), pp. 1-22, January 2009.
• Weighted Graph Cuts without Eigenvectors: A Multilevel Approach (pdf, software)
  I. Dhillon, Y. Guan, B. Kulis.
  IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI) 29(11), pp. 1944-1957, November 2007.
• A Fast Kernel-based Multilevel Algorithm for Graph Clustering (pdf, software)
  I. Dhillon, B. Kulis.
  In ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), pp. 629-634, August 2005.
• Semi-supervised Graph Clustering: A Kernel Approach (pdf)
  B. Kulis, S. Basu, I. Dhillon, R. Mooney.
  In International Conference on Machine Learning (ICML), pp. 457-464, July 2005.
• Kernel k-means, Spectral Clustering and Normalized Cuts (pdf, software)
  I. Dhillon, Y. Guan, B. Kulis.
  In ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), pp. 551-556, August 2004.
  (A longer version appears as UTCS Technical Report #TR-04-25, June 30, 2004.)