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, software)
  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, software)
  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, software)
  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, software)
  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, software)
  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, software)
  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, software)
  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, software)
  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, software)
  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, software)
  W. Tang, Z. Lu, I. Dhillon.
  In IEEE International Conference on Data Mining (ICDM), December 2009.
• Semi-Supervised Graph Clustering: A Kernel Approach (pdf, software)
  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, software)
  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.)