DBLP: Ian Davidson

	2013
i3		Ian Davidson: Minimum Message Length Clustering Using Gibbs Sampling. CoRR abs/1301.3851 (2013)
	2012
j7		Rita Chattopadhyay, Qian Sun, Wei Fan, Ian Davidson, Sethuraman Panchanathan, Jieping Ye: Multisource domain adaptation and its application to early detection of fatigue. TKDD 6(4): 18 (2012)
c43		Xiang Wang, Buyue Qian, Ian Davidson: Improving document clustering using automated machine translation. CIKM 2012: 645-653
c42		Xiang Wang, Buyue Qian, Ian Davidson: Labels vs. Pairwise Constraints: A Unified View of Label Propagation and Constrained Spectral Clustering. ICDM 2012: 1146-1151
c41		Goutam Paul, Ian Davidson, Imon Mukherjee, S. S. Ravi: Keyless Steganography in Spatial Domain Using Energetic Pixels. ICISS 2012: 134-148
c40		Rita Chattopadhyay, Zheng Wang, Wei Fan, Ian Davidson, Sethuraman Panchanathan, Jieping Ye: Batch mode active sampling based on marginal probability distribution matching. KDD 2012: 741-749
c39		Ian Davidson: Two approaches to understanding when constraints help clustering. KDD 2012: 1312-1320
i2		Xiang Wang, Buyue Qian, Ian Davidson: On Constrained Spectral Clustering and Its Applications. CoRR abs/1201.5338 (2012)
i1		Buyue Qian, Xiang Wang, Ian Davidson: A Reconstruction Error Formulation for Semi-Supervised Multi-task and Multi-view Learning. CoRR abs/1202.0855 (2012)
	2011
c38		Rita Chattopadhyay, Jieping Ye, Sethuraman Panchanathan, Wei Fan, Ian Davidson: Multi-source domain adaptation and its application to early detection of fatigue. KDD 2011: 717-725
	2010
j6		Xiaoli Z. Fern, Ian Davidson, Jennifer G. Dy: MultiClust 2010: discovering, summarizing and using multiple clusterings. SIGKDD Explorations 12(2): 47-49 (2010)
c37		Buyue Qian, Ian Davidson: Semi-Supervised Dimension Reduction for Multi-Label Classification. AAAI 2010
c36		Xiang Wang, Ian Davidson: Active Spectral Clustering. ICDM 2010: 561-568
c35		Xiang Wang, Ian Davidson: Flexible constrained spectral clustering. KDD 2010: 563-572
c34		M. Shahriar Hossain, Satish Tadepalli, Layne T. Watson, Ian Davidson, Richard F. Helm, Naren Ramakrishnan: Unifying dependent clustering and disparate clustering for non-homogeneous data. KDD 2010: 593-602
c33		Ian Davidson, S. S. Ravi, Leonid Shamis: A SAT-based Framework for Efficient Constrained Clustering. SDM 2010: 94-105
	2009
j5		Ian Davidson, S. S. Ravi: Using instance-level constraints in agglomerative hierarchical clustering: theoretical and empirical results. Data Min. Knowl. Discov. 18(2): 257-282 (2009)
j4		Ian Davidson, Giri Kumar Tayi: Data preparation using data quality matrices for classification mining. European Journal of Operational Research 197(2): 764-772 (2009)
c32		Xiang Wang, Ian Davidson: Discovering Contexts and Contextual Outliers Using Random Walks in Graphs. ICDM 2009: 1034-1039
c31		Ian Davidson: Knowledge Driven Dimension Reduction for Clustering. IJCAI 2009: 1034-1039
c30		Zijie Qi, Ian Davidson: A principled and flexible framework for finding alternative clusterings. KDD 2009: 717-726
r1		Ian Davidson: Clustering with Constraints. Encyclopedia of Database Systems 2009: 393-396
	2008
c29		Ian Davidson, Zijie Qi: Finding Alternative Clusterings Using Constraints. ICDM 2008: 773-778
	2007
j3		Ian Davidson, S. S. Ravi: The complexity of non-hierarchical clustering with instance and cluster level constraints. Data Min. Knowl. Discov. 14(1): 25-61 (2007)
j2		Xingquan Zhu, Taghi M. Khoshgoftaar, Ian Davidson, Shichao Zhang: Editorial: Special issue on mining low-quality data. Knowl. Inf. Syst. 11(2): 131-136 (2007)
c28		Ian Davidson, S. S. Ravi: Intractability and clustering with constraints. ICML 2007: 201-208
c27		Ian Davidson, S. S. Ravi, Martin Ester: Efficient incremental constrained clustering. KDD 2007: 240-249
c26		Rong Ge, Martin Ester, Wen Jin, Ian Davidson: Constraint-driven clustering. KDD 2007: 320-329
c25		Wei Fan, Ian Davidson: On Sample Selection Bias and Its Efficient Correction via Model Averaging and Unlabeled Examples. SDM 2007
	2006
c24		Ian Davidson, S. S. Ravi: Identifying and Generating Easy Sets of Constraints for Clustering. AAAI 2006: 336-341
c23		Kiri Wagstaff, Sugato Basu, Ian Davidson: When Is Constrained Clustering Beneficial, and Why?. AAAI 2006
c22		Kun Zhang, Wei Fan, Xiaojing Yuan, Ian Davidson, Xiangshang Li: Forecasting Skewed Biased Stochastic Ozone Days: Analyses and Solutions. ICDM 2006: 753-764
c21		Wei Fan, Ian Davidson: Reverse testing: an efficient framework to select amongst classifiers under sample selection bias. KDD 2006: 147-156
c20		Ian Davidson, Kiri Wagstaff, Sugato Basu: Measuring Constraint-Set Utility for Partitional Clustering Algorithms. PKDD 2006: 115-126
c19		Ian Davidson, Wei Fan: When Efficient Model Averaging Out-Performs Boosting and Bagging. PKDD 2006: 478-486
	2005
c18		Minoo Aminian, Ian Davidson: Active Learning with Partially Labeled Data via Bias Reduction. FLAIRS Conference 2005: 810-811
c17		Wei Fan, Ian Davidson, Bianca Zadrozny, Philip S. Yu: An Improved Categorization of Classifier's Sensitivity on Sample Selection Bias. ICDM 2005: 605-608
c16		Ashwin Satyanarayana, Ian Davidson: A Dynamic Adaptive Sampling Algorithm (DASA) for Real World Applications: Finger Print Recognition and Face Recognition. ISMIS 2005: 631-640
c15		Ian Davidson, S. S. Ravi: Agglomerative Hierarchical Clustering with Constraints: Theoretical and Empirical Results. PKDD 2005: 59-70
c14		Ian Davidson, S. S. Ravi: Clustering with Constraints: Feasibility Issues and the k-Means Algorithm. SDM 2005
	2004
c13		Ian Davidson: An Ensemble Technique for Stable Learners with Performance Bounds. AAAI 2004: 330-335
c12		Ian Davidson, Minoo Aminian: Using the Central Limit Theorem for Belief Network Learning. AMAI 2004
c11		Ke Yin, Ian Davidson: Bayesian Model Averaging Across Model Spaces via Compact Encoding. AMAI 2004
c10		Ke Yin, Ian Davidson: An Information Theoretic Optimal Classifier for Semi-supervised Learning. IDEAL 2004: 740-745
c9		Ian Davidson, Minoo Aminian: Using the Central Limit Theorem for Belief Network Learning. ISAIM 2004
c8		Ke Yin, Ian Davidson: Bayesian Model Averaging Across Model Spaces via Compact Encoding. ISAIM 2004
c7		Ian Davidson, Goutam Paul: Locating secret messages in images. KDD 2004: 545-550
c6		Ian Davidson, Ashish Grover, Ashwin Satyanarayana, Giri Kumar Tayi: A general approach to incorporate data quality matrices into data mining algorithms. KDD 2004: 794-798
c5		Ke Yin, Ian Davidson: Further Applications of a Particle Visualization Framework. PAKDD 2004: 704-710
	2003
c4		George Berg, Ian Davidson, Ming-Yuan Duan, Goutam Paul: Searching for Hidden Messages: Automatic Detection of Steganography. IAAI 2003: 51-56
	2002
c3		Ian Davidson: Visualizing Clustering Results. SDM 2002
	2000
c2		Ian Davidson: Minimum Message Length Clustering Using Gibbs Sampling. UAI 2000: 160-167
	1996
c1		Arkadi Kosmynin, Ian Davidson: Using Background Contextual Knowledge for Document Representation. PODP 1996: 123-133
	1985
j1		Ian Davidson: Testing conformance to OSI standards. Computer Communications 8(4): 170-179 (1985)

2013

Ian Davidson: Minimum Message Length Clustering Using Gibbs Sampling. CoRR abs/1301.3851 (2013)

2012

Rita Chattopadhyay, Qian Sun, Wei Fan, Ian Davidson, Sethuraman Panchanathan, Jieping Ye: Multisource domain adaptation and its application to early detection of fatigue. TKDD 6(4): 18 (2012)

c43

Xiang Wang, Buyue Qian, Ian Davidson: Improving document clustering using automated machine translation. CIKM 2012: 645-653

c42

Xiang Wang, Buyue Qian, Ian Davidson: Labels vs. Pairwise Constraints: A Unified View of Label Propagation and Constrained Spectral Clustering. ICDM 2012: 1146-1151

c41

Goutam Paul, Ian Davidson, Imon Mukherjee, S. S. Ravi: Keyless Steganography in Spatial Domain Using Energetic Pixels. ICISS 2012: 134-148

c40

Rita Chattopadhyay, Zheng Wang, Wei Fan, Ian Davidson, Sethuraman Panchanathan, Jieping Ye: Batch mode active sampling based on marginal probability distribution matching. KDD 2012: 741-749

c39

Ian Davidson: Two approaches to understanding when constraints help clustering. KDD 2012: 1312-1320

Xiang Wang, Buyue Qian, Ian Davidson: On Constrained Spectral Clustering and Its Applications. CoRR abs/1201.5338 (2012)

Buyue Qian, Xiang Wang, Ian Davidson: A Reconstruction Error Formulation for Semi-Supervised Multi-task and Multi-view Learning. CoRR abs/1202.0855 (2012)

2011

c38

Rita Chattopadhyay, Jieping Ye, Sethuraman Panchanathan, Wei Fan, Ian Davidson: Multi-source domain adaptation and its application to early detection of fatigue. KDD 2011: 717-725

2010

Xiaoli Z. Fern, Ian Davidson, Jennifer G. Dy: MultiClust 2010: discovering, summarizing and using multiple clusterings. SIGKDD Explorations 12(2): 47-49 (2010)

c37

Buyue Qian, Ian Davidson: Semi-Supervised Dimension Reduction for Multi-Label Classification. AAAI 2010

c36

Xiang Wang, Ian Davidson: Active Spectral Clustering. ICDM 2010: 561-568

c35

Xiang Wang, Ian Davidson: Flexible constrained spectral clustering. KDD 2010: 563-572

c34

M. Shahriar Hossain, Satish Tadepalli, Layne T. Watson, Ian Davidson, Richard F. Helm, Naren Ramakrishnan: Unifying dependent clustering and disparate clustering for non-homogeneous data. KDD 2010: 593-602

c33

Ian Davidson, S. S. Ravi, Leonid Shamis: A SAT-based Framework for Efficient Constrained Clustering. SDM 2010: 94-105

2009

Ian Davidson, S. S. Ravi: Using instance-level constraints in agglomerative hierarchical clustering: theoretical and empirical results. Data Min. Knowl. Discov. 18(2): 257-282 (2009)

Ian Davidson, Giri Kumar Tayi: Data preparation using data quality matrices for classification mining. European Journal of Operational Research 197(2): 764-772 (2009)

c32

Xiang Wang, Ian Davidson: Discovering Contexts and Contextual Outliers Using Random Walks in Graphs. ICDM 2009: 1034-1039

c31

Ian Davidson: Knowledge Driven Dimension Reduction for Clustering. IJCAI 2009: 1034-1039

c30

Zijie Qi, Ian Davidson: A principled and flexible framework for finding alternative clusterings. KDD 2009: 717-726

Ian Davidson: Clustering with Constraints. Encyclopedia of Database Systems 2009: 393-396

2008

c29

Ian Davidson, Zijie Qi: Finding Alternative Clusterings Using Constraints. ICDM 2008: 773-778

2007

Ian Davidson, S. S. Ravi: The complexity of non-hierarchical clustering with instance and cluster level constraints. Data Min. Knowl. Discov. 14(1): 25-61 (2007)

Xingquan Zhu, Taghi M. Khoshgoftaar, Ian Davidson, Shichao Zhang: Editorial: Special issue on mining low-quality data. Knowl. Inf. Syst. 11(2): 131-136 (2007)

c28

Ian Davidson, S. S. Ravi: Intractability and clustering with constraints. ICML 2007: 201-208

c27

Ian Davidson, S. S. Ravi, Martin Ester: Efficient incremental constrained clustering. KDD 2007: 240-249

c26

Rong Ge, Martin Ester, Wen Jin, Ian Davidson: Constraint-driven clustering. KDD 2007: 320-329

c25

Wei Fan, Ian Davidson: On Sample Selection Bias and Its Efficient Correction via Model Averaging and Unlabeled Examples. SDM 2007

2006

c24

Ian Davidson, S. S. Ravi: Identifying and Generating Easy Sets of Constraints for Clustering. AAAI 2006: 336-341

c23

Kiri Wagstaff, Sugato Basu, Ian Davidson: When Is Constrained Clustering Beneficial, and Why?. AAAI 2006

c22

Kun Zhang, Wei Fan, Xiaojing Yuan, Ian Davidson, Xiangshang Li: Forecasting Skewed Biased Stochastic Ozone Days: Analyses and Solutions. ICDM 2006: 753-764

c21

Wei Fan, Ian Davidson: Reverse testing: an efficient framework to select amongst classifiers under sample selection bias. KDD 2006: 147-156

c20

Ian Davidson, Kiri Wagstaff, Sugato Basu: Measuring Constraint-Set Utility for Partitional Clustering Algorithms. PKDD 2006: 115-126

c19

Ian Davidson, Wei Fan: When Efficient Model Averaging Out-Performs Boosting and Bagging. PKDD 2006: 478-486

2005

c18

Minoo Aminian, Ian Davidson: Active Learning with Partially Labeled Data via Bias Reduction. FLAIRS Conference 2005: 810-811

c17

Wei Fan, Ian Davidson, Bianca Zadrozny, Philip S. Yu: An Improved Categorization of Classifier's Sensitivity on Sample Selection Bias. ICDM 2005: 605-608

c16

Ashwin Satyanarayana, Ian Davidson: A Dynamic Adaptive Sampling Algorithm (DASA) for Real World Applications: Finger Print Recognition and Face Recognition. ISMIS 2005: 631-640

c15

Ian Davidson, S. S. Ravi: Agglomerative Hierarchical Clustering with Constraints: Theoretical and Empirical Results. PKDD 2005: 59-70

c14

Ian Davidson, S. S. Ravi: Clustering with Constraints: Feasibility Issues and the k-Means Algorithm. SDM 2005

2004

c13

Ian Davidson: An Ensemble Technique for Stable Learners with Performance Bounds. AAAI 2004: 330-335

c12

Ian Davidson, Minoo Aminian: Using the Central Limit Theorem for Belief Network Learning. AMAI 2004

c11

Ke Yin, Ian Davidson: Bayesian Model Averaging Across Model Spaces via Compact Encoding. AMAI 2004

c10

Ke Yin, Ian Davidson: An Information Theoretic Optimal Classifier for Semi-supervised Learning. IDEAL 2004: 740-745

Ian Davidson, Minoo Aminian: Using the Central Limit Theorem for Belief Network Learning. ISAIM 2004

Ke Yin, Ian Davidson: Bayesian Model Averaging Across Model Spaces via Compact Encoding. ISAIM 2004

Ian Davidson, Goutam Paul: Locating secret messages in images. KDD 2004: 545-550

Ian Davidson, Ashish Grover, Ashwin Satyanarayana, Giri Kumar Tayi: A general approach to incorporate data quality matrices into data mining algorithms. KDD 2004: 794-798

Ke Yin, Ian Davidson: Further Applications of a Particle Visualization Framework. PAKDD 2004: 704-710

2003

George Berg, Ian Davidson, Ming-Yuan Duan, Goutam Paul: Searching for Hidden Messages: Automatic Detection of Steganography. IAAI 2003: 51-56

2002

Ian Davidson: Visualizing Clustering Results. SDM 2002

2000

Ian Davidson: Minimum Message Length Clustering Using Gibbs Sampling. UAI 2000: 160-167

1996

Arkadi Kosmynin, Ian Davidson: Using Background Contextual Knowledge for Document Representation. PODP 1996: 123-133

1985

Ian Davidson: Testing conformance to OSI standards. Computer Communications 8(4): 170-179 (1985)

1	Minoo Aminian	[c18] [c12] [c9]
2	Sugato Basu	[c23] [c20]
3	George Berg	[c4]
4	Rita Chattopadhyay	[j7] [c40] [c38]
5	Ming-Yuan Duan	[c4]
6	Jennifer G. Dy	[j6]
7	Martin Ester	[c27] [c26]
8	Wei Fan	[j7] [c40] [c38] [c25] [c22] [c21] [c19] [c17]
9	Xiaoli Z. Fern (Xiaoli Fern, Xiaoli Zhang Fern)	[j6]
10	Rong Ge	[c26]
11	Ashish Grover	[c6]
12	Richard F. Helm	[c34]
13	M. Shahriar Hossain	[c34]
14	Wen Jin	[c26]
15	Taghi M. Khoshgoftaar	[j2]
16	Arkadi Kosmynin	[c1]
17	Xiangshang Li	[c22]
18	Imon Mukherjee	[c41]
19	Sethuraman Panchanathan	[j7] [c40] [c38]
20	Goutam Paul	[c41] [c7] [c4]
21	Zijie Qi	[c30] [c29]
22	Buyue Qian	[c43] [c42] [i2] [i1] [c37]
23	Naren Ramakrishnan	[c34]
24	S. S. Ravi	[c41] [c33] [j5] [j3] [c28] [c27] [c24] [c15] [c14]
25	Ashwin Satyanarayana	[c16] [c6]
26	Leonid Shamis	[c33]
27	Qian Sun	[j7]
28	Satish Tadepalli	[c34]
29	Giri Kumar Tayi	[j4] [c6]
30	Kiri Wagstaff (Kiri L. Wagstaff)	[c23] [c20]
31	Xiang Wang	[c43] [c42] [i2] [i1] [c36] [c35] [c32]
32	Zheng Wang	[c40]
33	Layne T. Watson	[c34]
34	Jieping Ye	[j7] [c40] [c38]
35	Ke Yin	[c11] [c10] [c8] [c5]
36	Philip S. Yu	[c17]
37	Xiaojing Yuan	[c22]
38	Bianca Zadrozny	[c17]
39	Kun Zhang	[c22]
40	Shichao Zhang	[j2]
41	Xingquan Zhu	[j2]

Ian Davidson

Coauthor Index