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, Learning
Multiple Relative Attributes With Humans in the Loop B Qian, X Wang, N Cao, Y Jiang, I Davidson, Clinical
risk prediction with multilinear sparse logistic regression F Wang, P Zhang, B Qian, X Wang, I Davidson A
Reconstruction Error Based Framework for Multi-label and Multi-view Learning B Qian, X Wang, J Ye, I Davidson On
constrained spectral clustering and its applications X Wang, B Qian, I Davidson,
S Chakraborty, J Zhou, V Balasubramanian, S Panchanathan, I
Davidson, 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, Efficient
hierarchical clustering of large high dimensional datasets S Gilpin, B Qian, I Davidson, Batch
mode active sampling based on marginal probability distribution matching R Chattopadhyay, Z Wang, W Fan, I Davidson, S Panchanathan, J Ye, How
to ŇalternatizeÓ a clustering algorithm MS Hossain, N Ramakrishnan, I Davidson, LT Watson, Network
discovery via constrained tensor analysis of fmri data I Davidson, S Gilpin, O Carmichael, P Walker, Guided
learning for role discovery (glrd): Framework, algorithms, and applications S Gilpin, T Eliassi-Rad, I Davidson, Active
learning from relative queries B Qian, X Wang, F Wang, H Li, J Ye, I Davidson, Clustering
with Complex Constraints-Algorithms and Applications. W Zhi, X Wang, B Qian, P Butler, N Ramakrishnan, I Davidson Formalizing
hierarchical clustering as integer linear programming S Gilpin, S Nijssen, I Davidson, 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 Behavioral
event data and their analysis I Davidson, S Gilpin, PB Walker 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 The
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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
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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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