Publications

PhD Dissertation:

  1. K. Bhaduri. Efficient Local Algorithms for Distributed Data Mining in Large Scale Peer to Peer Environments: A Deterministic Approach . PhD Thesis. University of Maryland Baltimore County. May 2008. [pdf]


Journals:

  1. S. Das, K. Bhaduri, N. Oza, A. Srivastava. nu-Anomica: A Fast Support Vector based Novelty Detection Technique. (in communication). 2012.

  2. L. Ghaoui, G. Li, V. Duong, V. Pham, A. Srivastava, K. Bhaduri. Understanding Large Text Corpora via Sparse Machine Learning. Statistical Analysis and Data Mining Journal. (accepted). 2013.

  3. K. Das, K. Bhaduri, P. Votava. Distributed Anomaly Detection using 1-class SVM for Vertically Partitioned Data. Statistical Analysis and Data Mining Journal. Volume 4, Issue 4, pp. 393-406. August 2011. [pdf]

  4. K. Bhaduri, K. Das, K. Borne, C. Giannella, T. Mahule, H. Kargupta. Scalable, Asynchronous, Distributed Eigen-Monitoring of Astronomy Data Streams. Statistical Analysis and Data Mining Journal. Volume 4, Issue 3, pp. 336-352. June 2011. [pdf]

  5. K. Das, K. Bhaduri, H. Kargupta. Multi-objective Optimization Based Privacy Preserving Distributed Data Mining in Peer-to-peer Networks. Peer-to-Peer Networking and Applications. Volume 4, Issue 2, pp. 192-209. 2011. [pdf]

  6. K. Bhaduri, M. Stefanski, A. Srivastava. Privacy Preservation through Random Nonlinear Distortion. IEEE Transactions on Systems, Man and Cybernetics, Part B. Volume 41, Issue 1, pp. 260-272. 2011. [pdf]

  7. K. Das, K. Bhaduri, H. Kargupta. A Local Asynchronous Distributed Privacy Preserving Feature Selection Algorithm for Large Peer-to-Peer Networks. Knowledge and Information Systems Journal. Volume 24, Issue 3, pp. 341-367. September 2010. [pdf]

  8. R. Wolff, K. Bhaduri, H. Kargupta. A Generic Local Algorithm for Mining Data Streams in Large Distributed Systems. IEEE Transactions on Knowledge and Data Engineering. Volume 21, Issue 4, pp. 465-478. April 2009. [pdf]

  9. K. Bhaduri, H. Kargupta. A Scalable Local Algorithm for Distributed Multivariate Regression. Statistical Analysis and Data Mining Journal. Volume 1, Issue 3, pp. 177-194. November 2008. [pdf]

  10. K. Bhaduri, R. Wolff, C. Giannella, H. Kargupta. Distributed Decision Tree Induction in Peer-to-Peer Systems. Statistical Analysis and Data Mining. Volume 1, Issue 2, pp. 85-103. June 2008. [pdf]

  11. K. Das, K. Bhaduri, K. Liu, H. Kargupta. Distributed Identification of Top-l Inner Product Elements and its Application in a Peer-to-Peer Network. IEEE Transactions on Knowledge and Data Engineering. Volume 20, Issue 4, pp. 475-488. April 2008. [pdf]

  12. S. Datta, K. Bhaduri, C. Giannella, R. Wolff, H. Kargupta. Distributed Data Mining in Peer-to-Peer Networks. IEEE Internet Computing special issue on Distributed Data Mining. Volume 10, Number 4, pp. 18-26. 2006. [pdf]

  13. K. Liu, K. Bhaduri, K. Das, P. Nguyen, H. Kargupta. Client-side Web Mining for Community Formation in Peer-to-Peer Environments. SIGKDD Explorations. Volume 8, Issue 2, pp. 11-20. December 2006. [pdf]


Book Chapters:

  1. K. Bhaduri, M. Stolpe. Distributed Data Mining in Sensor Networks. A chapter in Managing and Mining Sensor Data, C. Aggarwal (editor), Springer. pp. 211-236. 2013.
  2. K. Das, K. Bhaduri. Parallel and Distributed Data Mining for Astronomy Applications. A chapter in Data Mining and Machine Learning for Astronomical Applications, K. Ali, A. Srivastava, J. Scargle and M. Way (editor), Chapman & Hall/CRC Press. pp. 595-616. 2012.

  3. K. Bhaduri, K. Das, K. Sivakumar, H. Kargupta, R. Wolff, R. Chen. Algorithms for Distributed Data Stream Mining. A chapter in Data Streams: Models and Algorithms, C. Aggarwal (editor), Springer. pp. 309-332. 2006.


Conferences and Workshops:

  1. M. Stolpe, K. Bhaduri, K. Das, K. Morik. Anomaly Detection in Large Data Sets by Vertically Distributed Core Vector Machines. (submitted). 2012.

  2. B. Matthews, S. Das, K. Bhaduri, K. Das, R. Martin, N. Oza, A. Srivastava, J. Stutz. Discovering Anomalous Aviation Safety Events using Scalable Data Mining Algorithms. (submitted). 2012.

  3. K. Das, A. Patil, K. Bhaduri, J Liu. EGraClus: Evolutionary graph clustering for dynamic networks. (submitted). 2012.

  4. K. Das, K. Bhaduri. ParitoSVR: Parallel Iterated Optimizer for Support Vector Regression in the Primal. (submitted). 2012.

  5. K. Bhaduri, K. Das, B. Matthews. Detecting Abnormal Machine Characteristics in Cloud Infrastructures. IEEE ICDM workshop KDCloud, Vancouver, Canada. pp. 137-144. 2011. [pdf]

  6. L. Ghaoui, G. Li, V. Duong, V. Pham, A. Srivastava, K. Bhaduri. Sparse Machine Learning Methods For Understanding Large Text Corpora. NASA Conference on Intelligent Data Understanding, Mountain View, CA. pp. 159-173. 2011. [pdf]

  7. K. Bhaduri, B. Matthews, C. Giannella. Algorithms for Speeding up Distance-based Outlier Detection. ACM SIGKDD Conference on Knowledge Discovery and Data Mining, San Diego. pp. 859-867. 2011.[pdf]

  8. K. Bhaduri, K. Das, C. Giannella. Distributed Monitoring of the R2 Statistic for Linear Regression. SIAM International Conference on Data Mining, Arizona. pp. 438-449. 2011. [pdf]

  9. K. Bhaduri, Q. Zhu, N. Oza, A. Srivastava. Fast and Flexible Multivariate Time Series Subsequence Search. IEEE International Conference on Data Mining, Sydney, Australia. pp. 48-57. 2010. [pdf]

  10. K. Bhaduri, K. Das, P. Votava. Distributed Anomaly Detection using Satellite Data From Multiple Modalities. NASA Conference on Intelligent Data Understanding, Mountain View, CA. pp. 109-123. 2010. [pdf]

  11. K. Bhaduri, A. Srivastava. A Local Scalable Distributed Expectation Maximization Algorithm for Large Peer-to-Peer Networks. IEEE International Conference on Data Mining, Miami. pp. 31-40. 2009. [pdf]

  12. S. Das, K. Bhaduri, N. Oza, A. Srivastava. nu-Anomica: A Fast Support Vector based Novelty Detection Technique. IEEE International Conference on Data Mining, Miami. pp. 101-109. 2009. [pdf]

  13. S. Das, B. Matthews, K. Bhaduri, N. Oza, A. Srivastava. Detecting Anomalies in Multivariate Data Sets with Switching Sequences and Continuous Streams. NIPS 2009 Workshop on Understanding Multiple Kernel Learning Methods, Vancouver. 2009.

  14. K. Das, K. Bhaduri, H. Kargupta. A Local Distributed Peer-to-Peer Algorithm Using Multi-Party Optimization Based Privacy Preservation for Data Mining Primitive Computation. IEEE International Conference on Peer-to-Peer Computing, Seattle. pp. 212-221. 2009. (Invited for a fast track submission to Springer Journal on Peer-to-Peer Networking and Applications (PPNA), as one of the outstanding papers of P2P'09). [pdf]

  15. K. Das, K. Bhaduri, S. Arora, W. Griffin, K. Borne, C. Giannella, H. Kargupta. Scalable Distributed Change Detection from Astronomy Data Streams using Local, Asynchronous Eigen Monitoring Algorithms. SIAM International Conference on Data Mining, Nevada. pp 245-256. 2009. [pdf]

  16. K. Bhaduri, H. Kargupta. An Efficient Local Algorithm for Distributed Multivariate Regression in Peer-to-Peer Networks. SIAM International Conference on Data Mining, Atlanta. pp. 153-164. 2008. (Best of SDM'08, 6 out of 282 submissions). [pdf]

  17. R. Wolff, K. Bhaduri, H. Kargupta. Local L2 Thresholding Based Data Mining in Peer-to-Peer Systems. SIAM International Conference in Data Mining, Maryland, USA. pp. 430-441. 2006. [pdf]

  18. K. Liu, K. Bhaduri, K. Das, P. Nguyen, H. Kargupta. Client-side Web Mining for Community Formation in Peer-to-Peer Environments. SIGKDD workshop on web usage and analysis (WebKDD). Philadelphia, Pennsylvania, USA. 2006. (Selected as the most interesting paper from the WebKDD workshop) [pdf]

  19. K. Bhaduri, K. Das, H. Kargupta. Peer-to-Peer Data Mining, Privacy Issues, and Games. Autonomous Intelligent Systems: Agents and Data Mining. V. Gorodetsky, C. Zhang, V. Skormin, L. Cao (Editors), LNAI 4476, Springer. pp. 1-10. 2007. [pdf]