Papers in Last Three Years


A Framework for Minimal Clustering Modification via Constraint Programming.

T. Kuo, I Davidson, AAAI 17


Probabilistic Formulations of Regression with Mixed Guidance

A Gress, I Davidson, IEEE ICDM 16


Some Advances in Role Discovery in Graphs

S Gilpin, I Davidson, Arxiv


A framework for actionable clustering using constraint programming

B. Duong, C. Vrain, I. Davidson, ECAI 2016.


Scalable fast rank-1 dictionary learning for fmri big data analysis

J. Ye, I. Davidson, KDD 2016


Accelerating online cp decompositions for higher order tensors

J Bailey, I Davidson KDD 2016


A Framework for Outlier Description Using Constraint Programming.

T Kuo, I Davidson, AAAI 2016


Accurate Estimation of Generalization Performance for Active Learning

A Gress, I Davidson, IEEE ICDM 2015.

Unified and contrasting cuts in multiple graphs: Application to medical imaging segmentation

T Kuo, I Davidson, KDD 2015


Structural graphical lasso for learning mouse brain connectivity

J Ye, I Davidson, KDD 2015


A flexible ILP formulation for hierarchical clustering

S Gilpin, I Davidson AIJ


A Framework for Simplifying Trip Data into Networks via Coupled Matrix Factorization

CT Kuo, J Bailey, I Davidson, SIAM DM 2015

 

A Flexible Framework for Projecting Heterogeneous Data

A Gress, I Davidson, Proceedings of the 23rd ACM International Conference on Conference on  Knowledge Information and Management

 

Learning Multiple Relative Attributes With Humans in the Loop

B Qian, X Wang, N Cao, Y Jiang, I Davidson, IEEE Transactiions  on Information Processing

 

Clinical risk prediction with multilinear sparse logistic regression

F Wang, P Zhang, B Qian, X Wang, I Davidson, Proceedings of the 20th ACM SIGKDD international conference on Knowledgedge Discovery and Data Mining

 

A Reconstruction Error Based Framework for Multi-label and Multi-view Learning

B Qian, X Wang, J Ye, I Davidson, IEEE Transactions on Knowledge and Data Engineering

 

On constrained spectral clustering and its applications

X Wang, B Qian, I Davidson, Data Mining and Knowledge Discovery 28 (1), 1-30

 

Active Matrix Completion

S Chakraborty, J Zhou, V Balasubramanian, S Panchanathan, I Davidson, Data Mining (ICDM), 2013 IEEE 13th International Conference on, 81-90

 

Fast pairwise query selection for large-scale active learning to rank

B Qian, X Wang, J Wang, H Li, N Cao, W Zhi, I Davidson, Data Mining (ICDM), 2013 IEEE 13th International Conference on, 607-616

 

Efficient hierarchical clustering of large high dimensional datasets

S Gilpin, B Qian, I Davidson, Proceedings of the 22nd ACM international conference on Conference on Knowledge Information and Management 2013

 

Batch mode active sampling based on marginal probability distribution matching

R Chattopadhyay, Z Wang, W Fan, I Davidson, S Panchanathan, J Ye, ACM Transactions on Knowledge Discovery from Data (TKDD) 7 (3), 13

 

How to ŇalternatizeÓ a clustering algorithm

MS Hossain, N Ramakrishnan, I Davidson, LT Watson, Data Mining and Knowledge Discovery 27 (2), 193-224

 

Network discovery via constrained tensor analysis of fmri data

I Davidson, S Gilpin, O Carmichael, P Walker, Proceedings of the 19th ACM SIGKDD international conference on Knowledgedge Discovery and  Data Mining 2013

 

Guided learning for role discovery (glrd): Framework, algorithms, and applications

S Gilpin, T Eliassi-Rad, I Davidson, Proceedings of the 19th ACM SIGKDD international conference on Knowledge  Discovery and  Data Mining 2013

 

Active learning from relative queries

B Qian, X Wang, F Wang, H Li, J Ye, I Davidson, Proceedings of the Twenty-Third international joint conference on Artificial Intelligence


 

Clustering with Complex Constraints-Algorithms and Applications.

W Zhi, X Wang, B Qian, P Butler, N Ramakrishnan, I Davidson, Proceedings of the twenty-seventh AAAI conference on artificial intelligence  (AAAI 2013)

 

Formalizing hierarchical clustering as integer linear programming

S Gilpin, S Nijssen, I Davidson, Proceedings of the twenty-seventh AAAI conference on artificial intelligence  (AAAI 2013)

 

Active learning to rank using pairwise supervision

B Qian, H Li, J Wang, X Wang, I Davidson, Proc. SIAM Int. Conf. Data Mining 2013.

 

Multi-objective multi-view spectral clustering via pareto optimization

X Wang, B Qian, J Ye, I Davidson, Proc. SIAM Int. Conf. Data Mining 2013.

 

Behavioral event data and their analysis

I Davidson, S Gilpin, PB Walker, Data Mining and Knowledge Discovery 25 (3), 635-653


Less Recent Papers

CIKM 2012 Paper on Multi-view Spectral Clustering for Text Documents


KDD 2012 Paper on Counting Feasible Clusterings


KDD 2011 Paper on Constrained Hierarchies PDF


KDD 2011 Paper on Multi source learning PDF


KDD 2010 Paper on Constrained Spectral Clustering PDF


KDD 2010 Paper on Disparate Clustering PDF


ICDM 2010 Paper on Contextual Outliers PDF


ICDM 2009 Paper on Active Spectral Clustering PDF


AAAI 2010 Paper on Multi-label, Semi-Supervised Learning PDF


SDM 2010 Paper on SAT Solvers and Clustering PDF


New DMKD Journal Paper on Constraints and Hierarchical Clustering PDF


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New IJCAI Paper on Dimension Reduction Using Weighted Graphs PDF


New KDD Paper on Finding Alternative Clusterings PDF


New ICDM Paper on Finding Alternative Clusterings PDF


New Journal of DMKD Paper on Constraints and Agglomerative clustering: PDF


The Book has been sent to the publishers, check it out! Click here for book details, Buy from Amazon


 Popular Papers


Davidson I. Ester M. and Ravi, S.S., Efficient Incremental Clustering with Constraints, 13th ACM Knowledge Discovery and Data Mining Conference 2007 PDF


Davidson I., Ravi, S.S., Intractability and Clustering with Constraints, To Appear in the Proceeding of ICML 2007 PDF


Davidson I., Basu S.S., Clustering with Constraints Bibliography, To Appear, PDF


Davidson I., Wagstaff, K., Basu, Sugato., Measuring Constraint-Set Utility for Partitional Clustering Algorithms , To Appear in the Proceeding of ECML/PKDD 2006 (acceptance rate 9%) PDF,


Davidson I., Ravi S.S., Identifying and Generating Easy Sets of Constraints For Clustering, To Appear 21st AAAI Conference, 2006. (acceptance rate 21%) PDF  


Davidson I. and Ravi, S. S. Hierarchical Clustering with Constraints: Theory and Practice, 9th European Principles and Practice of KDD, PKDD 2005. (acceptance rate 11%) (Email me for Journal/TR version) PDF Extended technical report with all proofs PDF


Davidson I., Ravi, S.S., Clustering under Constraints: Feasibility Issues and the $K$-Means Algorithm, 5th SIAM Data Mining Conference, (acceptance rate 14%). Winner, Best Paper Award, PDF,


Learning With Biased Training Sets (In collaboration with Wei Fan (IBM Watson))

Wei Fan and Ian Davidson "On Sample Selection Bias and Its Efficient Correction via Model Averaging and Unlabeled Examples", SIAM Data Mining Conference 2007 (acceptance rate 9%).


Kun Zhang, Wei Fan, Xiaojing Yuan, Ian Davidson, and Xiangshang Li, "Forecasting Skewed Biased Stochastic Ozone Days", IEEE ICDM 2006 (acceptance rate 9%). , Winner Best Paper Award, PDF,


Fan W., Davidson I., Zadrozny B. and Yu P., An Improved Categorization of Classifier's Sensitivity on Sample Selection Bias, 5th IEEE International Conference on Data Mining, ICDM 2005. (acceptance rate 18%) PDF  

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