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Semantic ScholarPang-Ning Tan
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- affiliation: Michigan State University, East Lansing, USA
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2010 – today
- 2017
[j14]Jianpeng Xu, Pang-Ning Tan, Jiayu Zhou, Lifeng Luo:
Online Multi-Task Learning Framework for Ensemble Forecasting. IEEE Trans. Knowl. Data Eng. 29(6): 1268-1280 (2017)- [c74]Shuai Yuan, Pang-Ning Tan, Kendra Spence Cheruvelil, C. Emi Fergus, Nicholas K. Skaff, Patricia A. Soranno:
Hash-Based Feature Learning for Incomplete Continuous-Valued Data. SDM 2017: 678-686 - [c73]Xi Liu, Pang-Ning Tan, Lei Liu, Steven J. Simske:
Automated classification of EEG signals for predicting students' cognitive state during learning. WI 2017: 442-450 - [c72]Courtland VanDam, Jiliang Tang, Pang-Ning Tan:
Understanding compromised accounts on Twitter. WI 2017: 737-744 - 2016
- [c71]Jianpeng Xu, Jiayu Zhou, Pang-Ning Tan, Xi Liu, Lifeng Luo:
WISDOM: Weighted incremental spatio-temporal multi-task learning via tensor decomposition. BigData 2016: 522-531 - [c70]Ding Wang, Prakash Mandayam Comar, Pang-Ning Tan:
Crowdsourcing of network data. IJCNN 2016: 2204-2211 - [c69]Xi Liu, Han Hee Song, Mario Baldi, Pang-Ning Tan:
Macro-scale mobile app market analysis using customized hierarchical categorization. INFOCOM 2016: 1-9 - [c68]Jianpeng Xu, Kaixiang Lin, Pang-Ning Tan, Jiayu Zhou:
Synergies that Matter: Efficient Interaction Selection via Sparse Factorization Machine. SDM 2016: 108-116 - [c67]Jianpeng Xu, Pang-Ning Tan, Lifeng Luo, Jiayu Zhou:
GSpartan: a Geospatio-Temporal Multi-task Learning Framework for Multi-location Prediction. SDM 2016: 657-665 - [c66]
- 2015
- [c65]
- [c64]Shuai Yuan, Pang-Ning Tan, Kendra Spence Cheruvelil, Sarah M. Collins, Patricia A. Soranno:
Constrained spectral clustering for regionalization: Exploring the trade-off between spatial contiguity and landscape homogeneity. DSAA 2015: 1-10 - [c63]Jianpeng Xu, Jiayu Zhou, Pang-Ning Tan:
FORMULA: FactORized MUlti-task LeArning for task discovery in personalized medical models. SDM 2015: 496-504 - 2014
- [j13]Zubin Abraham, Pang-Ning Tan, Perdinan, Julie A. Winkler, Shiyuan Zhong, Malgorzata Liszewska:
Contour regression: A distribution-regularized regression framework for climate modeling. Statistical Analysis and Data Mining 7(4): 272-281 (2014) - [c62]Lei Liu, Sabyasachi Saha, Ruben Torres, Jianpeng Xu, Pang-Ning Tan, Antonio Nucci, Marco Mellia:
Detecting malicious clients in ISP networks using HTTP connectivity graph and flow information. ASONAM 2014: 150-157 - [c61]Jianpeng Xu, Pang-Ning Tan, Lifeng Luo:
ORION: Online Regularized Multi-task Regression and Its Application to Ensemble Forecasting. ICDM 2014: 1061-1066 - [e3]
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FacebookMohammed Javeed Zaki, Zoran Obradovic, Pang-Ning Tan, Arindam Banerjee, Chandrika Kamath, Srinivasan Parthasarathy:
Proceedings of the 2014 SIAM International Conference on Data Mining, Philadelphia, Pennsylvania, USA, April 24-26, 2014. SIAM 2014, ISBN 978-1-61197-344-0 [contents]
Proceedings of the 2014 SIAM International Conference on Data Mining, Philadelphia, Pennsylvania, USA, April 24-26, 2014. SIAM 2014, ISBN 978-1-61197-344-0 [contents]
[c60]
Prakash Mandayam Comar, Lei Liu, Sabyasachi Saha, Pang-Ning Tan, Antonio Nucci:
Combining supervised and unsupervised learning for zero-day malware detection. INFOCOM 2013: 2022-2030
Combining supervised and unsupervised learning for zero-day malware detection. INFOCOM 2013: 2022-2030
[c59]
Zubin Abraham, Pang-Ning Tan, Perdinan, Julie Winkler, Shiyuan Zhong, Malgorzata Liszewska:
Position Preserving Multi-Output Prediction. ECML/PKDD (2) 2013: 320-335
Position Preserving Multi-Output Prediction. ECML/PKDD (2) 2013: 320-335
[c58]
Lei Liu, Prakash Mandayam Comar, Antonio Nucci, Sabyasachi Saha, Pang-Ning Tan:
Missing or Inapplicable: Treatment of Incomplete Continuous-valued Features in Supervised Learning. SDM 2013: 46-54
Missing or Inapplicable: Treatment of Incomplete Continuous-valued Features in Supervised Learning. SDM 2013: 46-54
[c57]
Zubin Abraham, Malgorzata Liszewska, Perdinan, Pang-Ning Tan, Julie Winkler, Shiyuan Zhong:
Distribution Regularized Regression Framework for Climate Modeling. SDM 2013: 333-341
Distribution Regularized Regression Framework for Climate Modeling. SDM 2013: 333-341
[p1]
Ronald Nussbaum, Abdol-Hossein Esfahanian, Pang-Ning Tan:
Clustering Social Networks Using Distance-Preserving Subgraphs. The Influence of Technology on Social Network Analysis and Mining 2013: 331-349
Clustering Social Networks Using Distance-Preserving Subgraphs. The Influence of Technology on Social Network Analysis and Mining 2013: 331-349
[j12]
Prakash Mandayam Comar, Pang-Ning Tan, Anil K. Jain:
Simultaneous classification and community detection on heterogeneous network data. Data Min. Knowl. Discov. 25(3): 420-449 (2012)
Simultaneous classification and community detection on heterogeneous network data. Data Min. Knowl. Discov. 25(3): 420-449 (2012)
[j11]
Prakash Mandayam Comar, Pang-Ning Tan, Anil K. Jain:
A framework for joint community detection across multiple related networks. Neurocomputing 76(1): 93-104 (2012)
A framework for joint community detection across multiple related networks. Neurocomputing 76(1): 93-104 (2012)
[c56]
Prakash Mandayam Comar, Lei Liu, Sabyasachi Saha, Antonio Nucci, Pang-Ning Tan:
Weighted linear kernel with tree transformed features for malware detection. CIKM 2012: 2287-2290
Weighted linear kernel with tree transformed features for malware detection. CIKM 2012: 2287-2290
[c55]
Lei Liu, Prakash Mandayam Comar, Sabyasachi Saha, Pang-Ning Tan, Antonio Nucci:
Recursive NMF: Efficient label tree learning for large multi-class problems. ICPR 2012: 2148-2151
Recursive NMF: Efficient label tree learning for large multi-class problems. ICPR 2012: 2148-2151
[e2]
Pang-Ning Tan, Sanjay Chawla, Chin Kuan Ho, James Bailey:
Advances in Knowledge Discovery and Data Mining - 16th Pacific-Asia Conference, PAKDD 2012, Kuala Lumpur, Malaysia, May 29-June 1, 2012, Proceedings, Part I. Lecture Notes in Computer Science 7301, Springer 2012, ISBN 978-3-642-30216-9 [contents]
Advances in Knowledge Discovery and Data Mining - 16th Pacific-Asia Conference, PAKDD 2012, Kuala Lumpur, Malaysia, May 29-June 1, 2012, Proceedings, Part I. Lecture Notes in Computer Science 7301, Springer 2012, ISBN 978-3-642-30216-9 [contents]
[e1]
Pang-Ning Tan, Sanjay Chawla, Chin Kuan Ho, James Bailey:
Advances in Knowledge Discovery and Data Mining - 16th Pacific-Asia Conference, PAKDD 2012, Kuala Lumpur, Malaysia, May 29 - June 1, 2012, Proceedings, Part II. Lecture Notes in Computer Science 7302, Springer 2012, ISBN 978-3-642-30219-0 [contents]
Advances in Knowledge Discovery and Data Mining - 16th Pacific-Asia Conference, PAKDD 2012, Kuala Lumpur, Malaysia, May 29 - June 1, 2012, Proceedings, Part II. Lecture Notes in Computer Science 7302, Springer 2012, ISBN 978-3-642-30219-0 [contents]
[j10]
Samah Jamal Fodeh, William F. Punch, Pang-Ning Tan:
On ontology-driven document clustering using core semantic features. Knowl. Inf. Syst. 28(2): 395-421 (2011)
On ontology-driven document clustering using core semantic features. Knowl. Inf. Syst. 28(2): 395-421 (2011)
[c54]
Zubin Abraham, Pang-Ning Tan, Fan Xin:
Smoothed Quantile Regression for Statistical Downscaling of Extreme Events in Climate Modeling. CIDU 2011: 92-106
Smoothed Quantile Regression for Statistical Downscaling of Extreme Events in Climate Modeling. CIDU 2011: 92-106
[c53]
Prakash Mandayam Comar, Pang-Ning Tan, Anil K. Jain:
LinkBoost: A Novel Cost-Sensitive Boosting Framework for Community-Level Network Link Prediction. ICDM 2011: 131-140
LinkBoost: A Novel Cost-Sensitive Boosting Framework for Community-Level Network Link Prediction. ICDM 2011: 131-140
[c52]
Feilong Chen, Supranamaya Ranjan, Pang-Ning Tan:
Detecting bots via incremental LS-SVM learning with dynamic feature adaptation. KDD 2011: 386-394
Detecting bots via incremental LS-SVM learning with dynamic feature adaptation. KDD 2011: 386-394
[j9]
Jerry Scripps, Pang-Ning Tan:
Constrained overlapping clusters: minimizing the negative effects of bridge-nodes. Statistical Analysis and Data Mining 3(1): 20-37 (2010)
Constrained overlapping clusters: minimizing the negative effects of bridge-nodes. Statistical Analysis and Data Mining 3(1): 20-37 (2010)
[j8]
Haibin Cheng, Pang-Ning Tan, Rong Jin:
Efficient Algorithm for Localized Support Vector Machine. IEEE Trans. Knowl. Data Eng. 22(4): 537-549 (2010)
Efficient Algorithm for Localized Support Vector Machine. IEEE Trans. Knowl. Data Eng. 22(4): 537-549 (2010)
[c51]
Ronald Nussbaum, Abdol-Hossein Esfahanian, Pang-Ning Tan:
Clustering Social Networks Using Distance-Preserving Subgraphs. ASONAM 2010: 380-385
Clustering Social Networks Using Distance-Preserving Subgraphs. ASONAM 2010: 380-385
[c50]
Prakash Mandayam Comar, Pang-Ning Tan, Anil Kumar Jain:
Multi task learning on multiple related networks. CIKM 2010: 1737-1740
Multi task learning on multiple related networks. CIKM 2010: 1737-1740
[c49]
Zubin Abraham, Pang-Ning Tan:
An Integrated Framework for Simultaneous Classification and Regression of Time-Series Data. SDM 2010: 653-664
An Integrated Framework for Simultaneous Classification and Regression of Time-Series Data. SDM 2010: 653-664
[c48]
Lei Liu, Pang-Ning Tan:
A Framework for Co-classification of Articles and Users in Wikipedia. Web Intelligence 2010: 212-215
A Framework for Co-classification of Articles and Users in Wikipedia. Web Intelligence 2010: 212-215
[c47]
Prakash Mandayam Comar, Pang-Ning Tan, Anil Kumar Jain:
Identifying Cohesive Subgroups and Their Correspondences in Multiple Related Networks. Web Intelligence 2010: 476-483
Identifying Cohesive Subgroups and Their Correspondences in Multiple Related Networks. Web Intelligence 2010: 476-483
2000 – 2009
- 2009
- [c46]Jerry Scripps, Pang-Ning Tan, Feilong Chen, Abdol-Hossein Esfahanian:
A Matrix Alignment Approach for Collective Classification. ASONAM 2009: 155-159 - [c45]Ronald Nussbaum, Abdol-Hossein Esfahanian, Pang-Ning Tan:
History-Based Email Prioritization. ASONAM 2009: 364-365 - [c44]Feilong Chen, Pang-Ning Tan, Anil K. Jain:
A co-classification framework for detecting web spam and spammers in social media web sites. CIKM 2009: 1807-1810 - [c43]Zubin Abraham, Pang-Ning Tan:
A Semi-supervised Framework for Simultaneous Classification and Regression of Zero-Inflated Time Series Data with Application to Precipitation Prediction. ICDM Workshops 2009: 644-649 - [c42]Jerry Scripps, Pang-Ning Tan, Abdol-Hossein Esfahanian:
Measuring the effects of preprocessing decisions and network forces in dynamic network analysis. KDD 2009: 747-756 - [c41]Samah Jamal Fodeh, William F. Punch, Pang-Ning Tan:
Combining statistics and semantics via ensemble model for document clustering. SAC 2009: 1446-1450 - [c40]Haibin Cheng, Pang-Ning Tan, Christopher Potter, Steven A. Klooster:
Detection and Characterization of Anomalies in Multivariate Time Series. SDM 2009: 413-424 - [r4]Hui Xiong, Michael Steinbach, Pang-Ning Tan, Vipin Kumar, Wenjun Zhou:
Pattern Preserving Clustering. Encyclopedia of Data Warehousing and Mining 2009: 1505-1510 - [r3]
- [r2]
- 2008
- [j7]H. D. K. Moonesinghe, Pang-Ning Tan:
Outrank: a Graph-Based Outlier Detection Framework Using Random Walk. International Journal on Artificial Intelligence Tools 17(1): 19-36 (2008) - [c39]Haibin Cheng, Pang-Ning Tan, Christopher Potter, Steven A. Klooster:
Data mining for visual exploration and detection of ecosystem disturbances. GIS 2008: 60 - [c38]Haibin Cheng, Pang-Ning Tan, Christopher Potter, Steven A. Klooster:
A Robust Graph-Based Algorithm for Detection and Characterization of Anomalies in Noisy Multivariate Time Series. ICDM Workshops 2008: 349-358 - [c37]Jerry Scripps, Pang-Ning Tan, Feilong Chen, Abdol-Hossein Esfahanian:
A matrix alignment approach for link prediction. ICPR 2008: 1-4 - [c36]Haibin Cheng, Ruofei Zhang, Yefei Peng, Jianchang Mao, Pang-Ning Tan:
Maximum Margin Active Learning for Sequence Labeling with Different Length. ICDM 2008: 345-359 - [c35]Haibin Cheng, Pang-Ning Tan:
Semi-supervised learning with data calibration for long-term time series forecasting. KDD 2008: 133-141 - [c34]Feilong Chen, Jerry Scripps, Pang-Ning Tan:
Link Mining for a Social Bookmarking Web Site. Web Intelligence 2008: 169-175 - 2007
- [c33]Hamed Valizadegan, Pang-Ning Tan:
A Prototype-driven Framework for Change Detection in Data Stream Classification. CIDM 2007: 88-95 - [c32]Haibin Cheng, Pang-Ning Tan, Jon Sticklen, William F. Punch:
Recommendation via Query Centered Random Walk on K-Partite Graph. ICDM 2007: 457-462 - [c31]Jerry Scripps, Pang-Ning Tan, Abdol-Hossein Esfahanian:
Exploration of Link Structure and Community-Based Node Roles in Network Analysis. ICDM 2007: 649-654 - [c30]Samah Jamal Fodeh, Pang-Ning Tan:
Incorporating Background Knowledge for Subjective Rule Evaluation. ICTAI (2) 2007: 148-155 - [c29]H. D. K. Moonesinghe, Hamed Valizadegan, Samah Jamal Fodeh, Pang-Ning Tan:
A Probabilistic Substructure-Based Approach for Graph Classification. ICTAI (1) 2007: 346-349 - [c28]Hamed Valizadegan, Pang-Ning Tan:
Kernel Based Detection of Mislabeled Training Examples. SDM 2007: 309-319 - [c27]Haibin Cheng, Pang-Ning Tan, Rong Jin:
Localized Support Vector Machine and Its Efficient Algorithm. SDM 2007: 461-466 - 2006
- [j6]Hui Xiong, Pang-Ning Tan, Vipin Kumar:
Hyperclique pattern discovery. Data Min. Knowl. Discov. 13(2): 219-242 (2006) - [j5]Bo Wang, Sohraab Soltani, Jonathan K. Shapiro, Pang-Ning Tan:
Local Detection of Selfish Routing Behavior in Ad Hoc Networks. Journal of Interconnection Networks 7(1): 133-146 (2006) - [j4]Hui Xiong, Shashi Shekhar, Pang-Ning Tan, Vipin Kumar:
TAPER: A Two-Step Approach for All-Strong-Pairs Correlation Query in Large Databases. IEEE Trans. Knowl. Data Eng. 18(4): 493-508 (2006) - [c26]
- [c25]H. D. K. Moonesinghe, Samah Jamal Fodeh, Pang-Ning Tan:
Frequent Closed Itemset Mining Using Prefix Graphs with an Efficient Flow-Based Pruning Strategy. ICDM 2006: 426-435 - [c24]Brian D. Connelly, Christopher W. Bowron, Li Xiao, Pang-Ning Tan, Chen Wang:
Adaptively Routing P2P Queries Using Association Analysis. ICPP 2006: 281-288 - [c23]
- [c22]Haibin Cheng, Pang-Ning Tan, Jing Gao, Jerry Scripps:
Multistep-Ahead Time Series Prediction. PAKDD 2006: 765-774 - [c21]
- [c20]
- [c19]Jing Gao, Pang-Ning Tan, Haibin Cheng:
Semi-Supervised Clustering with Partial Background Information. SDM 2006: 489-493 - [c18]Jing Gao, Haibin Cheng, Pang-Ning Tan:
A Novel Framework for Incorporating Labeled Examples into Anomaly Detection. SDM 2006: 594-598 - 2005
- [b1]
Pang-Ning Tan, Michael Steinbach, Vipin Kumar:
Introduction to Data Mining. Addison-Wesley 2005, ISBN 0-321-32136-7 [contents]
Introduction to Data Mining. Addison-Wesley 2005, ISBN 0-321-32136-7 [contents]
[c17]
Bo Wang, Sohraab Soltani, Jonathan K. Shapiro, Pang-Ning Tan:
Local Detection of Selfish Routing Behavior in Ad Hoc Networks. ISPAN 2005: 392-399
Local Detection of Selfish Routing Behavior in Ad Hoc Networks. ISPAN 2005: 392-399
[c16]
Jing Gao, Jianzhong Li, Zhaogong Zhang, Pang-Ning Tan:
An Incremental Data Stream Clustering Algorithm Based on Dense Units Detection. PAKDD 2005: 420-425
An Incremental Data Stream Clustering Algorithm Based on Dense Units Detection. PAKDD 2005: 420-425
[j3]
Pang-Ning Tan, Vipin Kumar, Jaideep Srivastava:
Selecting the right objective measure for association analysis. Inf. Syst. 29(4): 293-313 (2004)
Selecting the right objective measure for association analysis. Inf. Syst. 29(4): 293-313 (2004)
[c15]
Behrouz Minaei-Bidgoli, Pang-Ning Tan, William F. Punch:
Mining interesting contrast rules for a web-based educational system. ICMLA 2004: 320-327
Mining interesting contrast rules for a web-based educational system. ICMLA 2004: 320-327
[c14]
Michael Steinbach, Pang-Ning Tan, Vipin Kumar:
Support envelopes: a technique for exploring the structure of association patterns. KDD 2004: 296-305
Support envelopes: a technique for exploring the structure of association patterns. KDD 2004: 296-305
[c13]
Hui Xiong, Shashi Shekhar, Pang-Ning Tan, Vipin Kumar:
Exploiting a support-based upper bound of Pearson's correlation coefficient for efficiently identifying strongly correlated pairs. KDD 2004: 334-343
Exploiting a support-based upper bound of Pearson's correlation coefficient for efficiently identifying strongly correlated pairs. KDD 2004: 334-343
[c12]
Michael Steinbach, Pang-Ning Tan, Hui Xiong, Vipin Kumar:
Generalizing the notion of support. KDD 2004: 689-694
Generalizing the notion of support. KDD 2004: 689-694
[c11]
[c10]
Aysel Ozgur, Pang-Ning Tan, Vipin Kumar:
RBA: An Integrated Framework for Regression based on Association Rules. SDM 2004: 210-221
RBA: An Integrated Framework for Regression based on Association Rules. SDM 2004: 210-221
[c9]
Hui Xiong, Michael Steinbach, Pang-Ning Tan, Vipin Kumar:
HICAP: Hierarchical Clustering with Pattern Preservation. SDM 2004: 279-290
HICAP: Hierarchical Clustering with Pattern Preservation. SDM 2004: 279-290
[r1]
Vipin Kumar, Pang-Ning Tan, Michael Steinbach:
Data Mining. Handbook of Data Structures and Applications 2004
Data Mining. Handbook of Data Structures and Applications 2004
[c8]
Hui Xiong, Pang-Ning Tan, Vipin Kumar:
Mining Strong Affinity Association Patterns in Data Sets with Skewed Support Distribution. ICDM 2003: 387-394
Mining Strong Affinity Association Patterns in Data Sets with Skewed Support Distribution. ICDM 2003: 387-394
[c7]
Michael Steinbach, Pang-Ning Tan, Vipin Kumar, Steven A. Klooster, Christopher Potter:
Discovery of climate indices using clustering. KDD 2003: 446-455
Discovery of climate indices using clustering. KDD 2003: 446-455
[j2]
Pang-Ning Tan, Vipin Kumar:
Discovery of Web Robot Sessions Based on their Navigational Patterns. Data Min. Knowl. Discov. 6(1): 9-35 (2002)
Discovery of Web Robot Sessions Based on their Navigational Patterns. Data Min. Knowl. Discov. 6(1): 9-35 (2002)
[c6]
Pang-Ning Tan, Vipin Kumar, Jaideep Srivastava:
Selecting the right interestingness measure for association patterns. KDD 2002: 32-41
Selecting the right interestingness measure for association patterns. KDD 2002: 32-41
[c5]
Vipin Kumar, Mahesh V. Joshi, Eui-Hong Han, Pang-Ning Tan, Michael Steinbach:
High Performance Data Mining. VECPAR 2002: 111-125
High Performance Data Mining. VECPAR 2002: 111-125
[c4]
[j1]
Jaideep Srivastava, Robert Cooley, Mukund Deshpande, Pang-Ning Tan:
Web Usage Mining: Discovery and Applications of Usage Patterns from Web Data. SIGKDD Explorations 1(2): 12-23 (2000)
Web Usage Mining: Discovery and Applications of Usage Patterns from Web Data. SIGKDD Explorations 1(2): 12-23 (2000)
[c3]
Pang-Ning Tan, Hannah Blau, Steven A. Harp, Robert P. Goldman:
Textual data mining of service center call records. KDD 2000: 417-423
Textual data mining of service center call records. KDD 2000: 417-423
[c2]
Pang-Ning Tan, Vipin Kumar, Jaideep Srivastava:
Indirect Association: Mining Higher Order Dependencies in Data. PKDD 2000: 632-637
Indirect Association: Mining Higher Order Dependencies in Data. PKDD 2000: 632-637
1990 – 1999
- 1999
- [c1]Robert Cooley, Pang-Ning Tan, Jaideep Srivastava:
Discovery of Interesting Usage Patterns from Web Data. WEBKDD 1999: 163-182
Coauthor Index
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last updated on 2017-08-16 19:04 CEST by the dblp team