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Ian Davidson
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- affiliation: University of California, Davis, USA
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2020 – today
- 2024
- [c111]Michael J. Livanos, Ian Davidson, Stephen Wong:
Cooperative Knowledge Distillation: A Learner Agnostic Approach. AAAI 2024: 14124-14131 - [c110]Ian Davidson, Michael J. Livanos, Antoine Gourru, Peter B. Walker, Julien Velcin, S. S. Ravi:
An Exemplars-Based Approach for Explainable Clustering: Complexity and Efficient Approximation Algorithms. SDM 2024: 46-54 - [c109]Michael J. Livanos, Ian Davidson:
Identification and Uses of Deep Learning Backbones via Pattern Mining. SDM 2024: 697-705 - [i26]Michael J. Livanos, Ian Davidson, Stephen Wong:
Cooperative Knowledge Distillation: A Learner Agnostic Approach. CoRR abs/2402.05942 (2024) - [i25]Michael J. Livanos, Ian Davidson:
Identification and Uses of Deep Learning Backbones via Pattern Mining. CoRR abs/2403.18278 (2024) - [i24]Ge Shi, Ziwen Kan, Jason Smucny, Ian Davidson:
ChaosMining: A Benchmark to Evaluate Post-Hoc Local Attribution Methods in Low SNR Environments. CoRR abs/2406.12150 (2024) - [i23]Michael J. Livanos, Ian Davidson:
Foundations for Unfairness in Anomaly Detection - Case Studies in Facial Imaging Data. CoRR abs/2407.19646 (2024) - 2023
- [j24]Ian Davidson, Zilong Bai
, Cindy Mylinh Tran, S. S. Ravi:
Making clusterings fairer by post-processing: algorithms, complexity results and experiments. Data Min. Knowl. Discov. 37(4): 1404-1440 (2023) - [j23]Xianli Zhang
, Buyue Qian
, Yang Li, Shilei Cao
, Ian Davidson:
Context-Aware and Time-Aware Attention-Based Model for Disease Risk Prediction With Interpretability. IEEE Trans. Knowl. Data Eng. 35(4): 3551-3562 (2023) - [c108]Ji Wang, Ding Lu, Ian Davidson, Zhaojun Bai:
Scalable Spectral Clustering with Group Fairness Constraints. AISTATS 2023: 6613-6629 - 2022
- [c107]Ge Shi
, Jason Smucny
, Ian Davidson:
Deep Learning for Prognosis Using Task-fMRI: A Novel Architecture and Training Scheme. KDD 2022: 1589-1597 - [i22]Ian Davidson, Michael J. Livanos, Antoine Gourru, Peter B. Walker, Julien Velcin, S. S. Ravi:
Explainable Clustering via Exemplars: Complexity and Efficient Approximation Algorithms. CoRR abs/2209.09670 (2022) - [i21]Ian Davidson, S. S. Ravi:
Towards Auditing Unsupervised Learning Algorithms and Human Processes For Fairness. CoRR abs/2209.11762 (2022) - [i20]Ji Wang, Ding Lu, Zhaojun Bai, Ian Davidson:
Scalable Spectral Clustering with Group Fairness Constraints. CoRR abs/2210.16435 (2022) - 2021
- [j22]Hongjing Zhang
, Tianyang Zhan, Sugato Basu, Ian Davidson:
A framework for deep constrained clustering. Data Min. Knowl. Discov. 35(2): 593-620 (2021) - [j21]Alex Mattenet, Ian Davidson, Siegfried Nijssen
, Pierre Schaus:
Generic Constraint-based Block Modeling using Constraint Programming. J. Artif. Intell. Res. 70: 597-630 (2021) - [j20]Hongjing Zhang, Tianyang Zhan, Ian Davidson:
A Self-Supervised Deep Learning Framework for Unsupervised Few-Shot Learning and Clustering. Pattern Recognit. Lett. 148: 75-81 (2021) - [c106]Hongjing Zhang, Ian Davidson:
Towards Fair Deep Anomaly Detection. FAccT 2021: 138-148 - [c105]Hongjing Zhang, Ian Davidson:
Deep Descriptive Clustering. IJCAI 2021: 3342-3348 - [c104]Ian Davidson:
Fairness and Explanation in Clustering and Outlier Detection. KDD 2021: 4037 - [e1]Carlotta Demeniconi, Ian Davidson:
Proceedings of the 2021 SIAM International Conference on Data Mining, SDM 2021, Virtual Event, April 29 - May 1, 2021. SIAM 2021, ISBN 978-1-61197-670-0 [contents] - [i19]Hongjing Zhang, Tianyang Zhan, Sugato Basu, Ian Davidson:
A Framework for Deep Constrained Clustering. CoRR abs/2101.02792 (2021) - [i18]Hongjing Zhang, Ian Davidson:
Deep Descriptive Clustering. CoRR abs/2105.11549 (2021) - [i17]Hongjing Zhang, Ian Davidson:
Deep Fair Discriminative Clustering. CoRR abs/2105.14146 (2021) - 2020
- [j19]Ian Davidson, Antoine Gourru, Julien Velcin, Yue Wu:
Behavioral differences: insights, explanations and comparisons of French and US Twitter usage during elections. Soc. Netw. Anal. Min. 10(1): 6 (2020) - [c103]Prathyush Sambaturu, Aparna Gupta, Ian Davidson, S. S. Ravi, Anil Vullikanti, Andrew Warren:
Efficient Algorithms for Generating Provably Near-Optimal Cluster Descriptors for Explainability. AAAI 2020: 1636-1643 - [c102]Ian Davidson, S. S. Ravi:
Making Existing Clusterings Fairer: Algorithms, Complexity Results and Insights. AAAI 2020: 3733-3740 - [c101]Alex Lucía Mattenet, Ian Davidson, Siegfried Nijssen
, Pierre Schaus:
Constraint Programming for an Efficient and Flexible Block Modeling Solver. AAAI 2020: 13685-13688 - [c100]Nguyen-Viet-Dung Nghiem, Christel Vrain, Thi-Bich-Hanh Dao, Ian Davidson:
Constrained Clustering via Post-processing. DS 2020: 53-67 - [c99]Ian Davidson, S. S. Ravi:
A Framework for Determining the Fairness of Outlier Detection. ECAI 2020: 2465-2472 - [c98]Nguyen-Viet-Dung Nghiem, Christel Vrain, Thi-Bich-Hanh Dao, Ian Davidson:
Post-traitement pour la classification probabiliste non supervisée sous contraintes. EGC 2020: 169-180 - [c97]Xianli Zhang, Buyue Qian, Shilei Cao, Yang Li, Hang Chen, Yefeng Zheng
, Ian Davidson:
INPREM: An Interpretable and Trustworthy Predictive Model for Healthcare. KDD 2020: 450-460 - [c96]Zilong Bai
, Hoa Nguyen
, Ian Davidson:
Block Model Guided Unsupervised Feature Selection. KDD 2020: 1201-1211 - [c95]Zilong Bai
, S. S. Ravi, Ian Davidson:
Towards Description of Block Model on Graph. ECML/PKDD (3) 2020: 37-53 - [c94]Hongjing Zhang, S. S. Ravi, Ian Davidson:
A Graph-Based Approach for Active Learning in Regression. SDM 2020: 280-288 - [i16]Hongjing Zhang, S. S. Ravi, Ian Davidson:
A Graph-Based Approach for Active Learning in Regression. CoRR abs/2001.11143 (2020) - [i15]Prathyush Sambaturu, Aparna Gupta, Ian Davidson, S. S. Ravi, Anil Vullikanti, Andrew Warren:
Efficient Algorithms for Generating Provably Near-Optimal Cluster Descriptors for Explainability. CoRR abs/2002.02487 (2020) - [i14]Zilong Bai, Hoa Nguyen
, Ian Davidson:
Block Model Guided Unsupervised Feature Selection. CoRR abs/2007.02376 (2020) - [i13]Hongjing Zhang, Ian Davidson:
Towards Fair Deep Anomaly Detection. CoRR abs/2012.14961 (2020)
2010 – 2019
- 2019
- [c93]Ian Davidson, Peter B. Walker:
Towards Fluid Machine Intelligence: Can We Make a Gifted AI? AAAI 2019: 9760-9764 - [c92]Alex Mattenet, Ian Davidson, Siegfried Nijssen, Pierre Schaus:
Generic Constraint-Based Block Modeling Using Constraint Programming. BNAIC/BENELEARN 2019 - [c91]Alex Mattenet, Ian Davidson, Siegfried Nijssen
, Pierre Schaus:
Generic Constraint-Based Block Modeling Using Constraint Programming. CP 2019: 656-673 - [c90]Jun Li, Yongjun Chen, Lei Cai, Ian Davidson, Shuiwang Ji
:
Dense Transformer Networks for Brain Electron Microscopy Image Segmentation. IJCAI 2019: 2894-2900 - [c89]Hongjing Zhang, Sugato Basu, Ian Davidson:
A Framework for Deep Constrained Clustering - Algorithms and Advances. ECML/PKDD (1) 2019: 57-72 - [c88]Jeremiah T. Folsom-Kovarik, Behrooz Mostafavi, Robert A. Sottilare, Ian Davidson, Ray Perez, Peter B. Walker:
Approaches to Enhancing Transfer of Training using Adaptive Instructional Systems. SoftCOM 2019: 1-6 - [i12]Bokun Wang, Ian Davidson:
Towards Fair Deep Clustering With Multi-State Protected Variables. CoRR abs/1901.10053 (2019) - [i11]Hongjing Zhang, Sugato Basu, Ian Davidson:
Deep Constrained Clustering - Algorithms and Advances. CoRR abs/1901.10061 (2019) - [i10]Yue Wu, Leman Akoglu, Ian Davidson:
Coverage-based Outlier Explanation. CoRR abs/1911.02617 (2019) - 2018
- [c87]Aubrey Gress, Ian Davidson:
Human Guided Linear Regression With Feature-Level Constraints. AAAI 2018: 3053-3060 - [c86]Minhao Cheng
, Ian Davidson, Cho-Jui Hsieh:
Extreme Learning to Rank via Low Rank Assumption. ICML 2018: 950-959 - [c85]Thi-Bich-Hanh Dao, Chia-Tung Kuo, S. S. Ravi, Christel Vrain, Ian Davidson:
Descriptive Clustering: ILP and CP Formulations with Applications. IJCAI 2018: 1263-1269 - [c84]Zilong Bai
, Buyue Qian, Ian Davidson:
Discovering Models from Structural and Behavioral Brain Imaging Data. KDD 2018: 1128-1137 - [c83]Ian Davidson, Antoine Gourru, S. S. Ravi:
The Cluster Description Problem - Complexity Results, Formulations and Approximations. NeurIPS 2018: 6193-6203 - [c82]Mohadeseh Ganji, Jeffrey Chan, Peter J. Stuckey, James Bailey, Christopher Leckie, Kotagiri Ramamohanarao, Ian Davidson:
Image Constrained Blockmodelling: A Constraint Programming Approach. SDM 2018: 19-27 - [c81]Zilong Bai
, Peter B. Walker, Ian Davidson:
Mixtures of Block Models for Brain Networks. SDM 2018: 46-54 - [r2]Ian Davidson:
Clustering with Constraints. Encyclopedia of Database Systems (2nd ed.) 2018 - [i9]Aubrey Gress, Ian Davidson:
Probabilistic Formulations of Regression with Mixed Guidance. CoRR abs/1804.01575 (2018) - [i8]Chia-Tung Kuo, Ian Davidson:
On The Equivalence of Tries and Dendrograms - Efficient Hierarchical Clustering of Traffic Data. CoRR abs/1810.05357 (2018) - 2017
- [j18]Sean Gilpin
, Ian Davidson:
A flexible ILP formulation for hierarchical clustering. Artif. Intell. 244: 95-109 (2017) - [j17]Goutam Paul, Ian Davidson, Imon Mukherjee
, S. S. Ravi:
Keyless dynamic optimal multi-bit image steganography using energetic pixels. Multim. Tools Appl. 76(5): 7445-7471 (2017) - [j16]Peter B. Walker, Jacob N. Norris, Anna E. Tschiffely, Melissa L. Mehalick, Craig A. Cunningham, Ian N. Davidson:
Applications of Transductive Spectral Clustering Methods in a Military Medical Concussion Database. IEEE ACM Trans. Comput. Biol. Bioinform. 14(3): 534-544 (2017) - [c80]Chia-Tung Kuo, S. S. Ravi, Thi-Bich-Hanh Dao, Christel Vrain, Ian Davidson:
A Framework for Minimal Clustering Modification via Constraint Programming. AAAI 2017: 1389-1395 - [c79]Aubrey Gress, Jeremiah T. Folsom-Kovarik, Ian Davidson:
Transfer Learning in Intelligent Tutoring Systems - Results, Challenges and New Directions. FLAIRS 2017: 555-560 - [c78]Shilei Cao, Buyue Qian, Changchang Yin, Xiaoyu Li, Jishang Wei, Qinghua Zheng, Ian Davidson:
Knowledge Guided Short-Text Classification for Healthcare Applications. ICDM 2017: 31-40 - [c77]Changchang Yin, Buyue Qian, Shilei Cao, Xiaoyu Li, Jishang Wei, Qinghua Zheng, Ian Davidson:
Deep Similarity-Based Batch Mode Active Learning with Exploration-Exploitation. ICDM 2017: 575-584 - [c76]Tao Zeng, Bian Wu, Jiayu Zhou, Ian Davidson, Shuiwang Ji
:
Recurrent Encoder-Decoder Networks for Time-Varying Dense Prediction. ICDM 2017: 1165-1170 - [c75]Weifeng Zhi, Buyue Qian, Ian Davidson:
Scalable Constrained Spectral Clustering via the Randomized Projected Power Method. ICDM 2017: 1201-1206 - [c74]Zilong Bai
, Peter B. Walker, Anna E. Tschiffely, Fei Wang, Ian Davidson:
Unsupervised Network Discovery for Brain Imaging Data. KDD 2017: 55-64 - [i7]Jun Li, Yongjun Chen, Lei Cai, Ian Davidson, Shuiwang Ji:
Dense Transformer Networks. CoRR abs/1705.08881 (2017) - [i6]Aubrey Gress, Ian Davidson:
Transfer Regression via Pairwise Similarity Regularization. CoRR abs/1712.08855 (2017) - 2016
- [c73]Chia-Tung Kuo, Ian Davidson:
A Framework for Outlier Description Using Constraint Programming. AAAI 2016: 1237-1243 - [c72]Thi-Bich-Hanh Dao, Christel Vrain, Khanh-Chuong Duong, Ian Davidson:
A Framework for Actionable Clustering Using Constraint Programming. ECAI 2016: 453-461 - [c71]Aubrey Gress, Ian Davidson:
Probabilistic Formulations of Regression with Mixed Guidance. ICDM 2016: 895-900 - [c70]Xiang Li
, Milad Makkie, Binbin Lin, Mojtaba Sedigh Fazli
, Ian Davidson, Jieping Ye, Tianming Liu, Shannon Quinn:
Scalable Fast Rank-1 Dictionary Learning for fMRI Big Data Analysis. KDD 2016: 511-519 - [c69]Shuo Zhou, Xuan Vinh Nguyen, James Bailey, Yunzhe Jia, Ian Davidson:
Accelerating Online CP Decompositions for Higher Order Tensors. KDD 2016: 1375-1384 - [i5]Sean Gilpin, Chia-Tung Kuo, Tina Eliassi-Rad, Ian Davidson:
Some Advances in Role Discovery in Graphs. CoRR abs/1609.02646 (2016) - 2015
- [j15]Fei Wang, Gregor Stiglic
, Zoran Obradovic, Ian Davidson:
Guest editorial: Special issue on data mining for medicine and healthcare. Data Min. Knowl. Discov. 29(4): 867-870 (2015) - [j14]Yan Sun, Ian Davidson:
Influential factors of online fraud occurrence in retailing banking sectors from a global prospective: An empirical study of individual customers in the UK and China. Inf. Comput. Secur. 23(1): 3-19 (2015) - [j13]Buyue Qian, Xiang Wang, Jieping Ye, Ian Davidson:
A Reconstruction Error Based Framework for Multi-Label and Multi-View Learning. IEEE Trans. Knowl. Data Eng. 27(3): 594-607 (2015) - [c68]Buyue Qian, Xiang Wang, Ian Davidson:
Propagating Ranking Functions on a Graph: Algorithms and Applications. AAAI 2015: 1833-1839 - [c67]Peter B. Walker, Sean Gilpin, Sidney G. Fooshee, Ian Davidson:
Constrained Tensor Decomposition via Guidance: Increased Inter and Intra-Group Reliability in fMRI Analyses. HCI (15) 2015: 361-369 - [c66]Aubrey Gress, Ian Davidson:
Accurate Estimation of Generalization Performance for Active Learning. ICDM 2015: 131-140 - [c65]Chia-Tung Kuo, Xiang Wang, Peter B. Walker, Owen T. Carmichael, Jieping Ye, Ian Davidson:
Unified and Contrasting Cuts in Multiple Graphs: Application to Medical Imaging Segmentation. KDD 2015: 617-626 - [c64]Sen Yang, Qian Sun, Shuiwang Ji
, Peter Wonka, Ian Davidson, Jieping Ye:
Structural Graphical Lasso for Learning Mouse Brain Connectivity. KDD 2015: 1385-1394 - [c63]Peter B. Walker, Ian Davidson:
Learning Automated Agents from Historical Game Data via Tensor Decomposition. SBP 2015: 213-221 - [c62]Peter B. Walker, Sidney G. Fooshee, Ian Davidson:
Complex Interactions in Social and Event Network Analysis. SBP 2015: 440-445 - [c61]Chia-Tung Kuo, James Bailey, Ian Davidson:
A Framework for Simplifying Trip Data into Networks via Coupled Matrix Factorization. SDM 2015: 739-747 - 2014
- [j12]Xiang Wang, Buyue Qian, Ian Davidson:
On constrained spectral clustering and its applications. Data Min. Knowl. Discov. 28(1): 1-30 (2014) - [j11]Buyue Qian, Xiang Wang, Nan Cao, Yu-Gang Jiang, Ian Davidson:
Learning Multiple Relative Attributes With Humans in the Loop. IEEE Trans. Image Process. 23(12): 5573-5585 (2014) - [c60]Aubrey Gress, Ian Davidson:
A Flexible Framework for Projecting Heterogeneous Data. CIKM 2014: 1169-1178 - [c59]Chia-Tung Kuo, Peter B. Walker, Owen T. Carmichael, Ian Davidson:
Spectral Clustering for Medical Imaging. ICDM 2014: 887-892 - [c58]Fei Wang, Ping Zhang
, Buyue Qian, Xiang Wang, Ian Davidson:
Clinical risk prediction with multilinear sparse logistic regression. KDD 2014: 145-154 - [c57]Xiang Wang, Jun Wang, Buyue Qian, Fei Wang, Ian Davidson:
Self-Taught Spectral Clustering via Constraint Augmentation. SDM 2014: 416-424 - [c56]Chia-Tung Kuo, Ian Davidson:
Directed Interpretable Discovery in Tensors with Sparse Projection. SDM 2014: 848-856 - [i4]Binbin Lin, Qingyang Li, Qian Sun, Ming-Jun Lai, Ian Davidson, Wei Fan, Jieping Ye:
Stochastic Coordinate Coding and Its Application for Drosophila Gene Expression Pattern Annotation. CoRR abs/1407.8147 (2014) - 2013
- [j10]Mahmud Shahriar Hossain, Naren Ramakrishnan
, Ian Davidson, Layne T. Watson:
How to "alternatize" a clustering algorithm. Data Min. Knowl. Discov. 27(2): 193-224 (2013) - [j9]Rita Chattopadhyay, Zheng Wang, Wei Fan, Ian Davidson, Sethuraman Panchanathan, Jieping Ye:
Batch Mode Active Sampling Based on Marginal Probability Distribution Matching. ACM Trans. Knowl. Discov. Data 7(3): 13:1-13:25 (2013) - [c55]Sean Gilpin, Siegfried Nijssen, Ian N. Davidson:
Formalizing Hierarchical Clustering as Integer Linear Programming. AAAI 2013: 372-378 - [c54]Weifeng Zhi, Xiang Wang, Buyue Qian, Patrick Butler, Naren Ramakrishnan, Ian Davidson:
Clustering with Complex Constraints - Algorithms and Applications. AAAI 2013: 1056-1062 - [c53]Sean Gilpin, Buyue Qian, Ian Davidson:
Efficient hierarchical clustering of large high dimensional datasets. CIKM 2013: 1371-1380 - [c52]Henry L. Phillips, Peter B. Walker, Carrie H. Kennedy, Owen T. Carmichael, Ian N. Davidson:
Guided Learning Algorithms: An Application of Constrained Spectral Partitioning to Functional Magnetic Resonance Imaging (fMRI). HCI (24) 2013: 709-716 - [c51]Shayok Chakraborty, Jiayu Zhou, Vineeth Nallure Balasubramanian
, Sethuraman Panchanathan, Ian Davidson, Jieping Ye:
Active Matrix Completion. ICDM 2013: 81-90 - [c50]Buyue Qian, Xiang Wang, Jun Wang, Hongfei Li, Nan Cao, Weifeng Zhi, Ian Davidson:
Fast Pairwise Query Selection for Large-Scale Active Learning to Rank. ICDM 2013: 607-616 - [c49]Rita Chattopadhyay, Wei Fan, Ian Davidson, Sethuraman Panchanathan, Jieping Ye:
Joint Transfer and Batch-mode Active Learning. ICML (3) 2013: 253-261 - [c48]Buyue Qian, Xiang Wang, Fei Wang, Hongfei Li, Jieping Ye, Ian Davidson:
Active Learning from Relative Queries. IJCAI 2013: 1614-1620 - [c47]Sean Gilpin, Tina Eliassi-Rad, Ian N. Davidson:
Guided learning for role discovery (GLRD): framework, algorithms, and applications. KDD 2013: 113-121 - [c46]Ian N. Davidson, Sean Gilpin, Owen T. Carmichael, Peter B. Walker:
Network discovery via constrained tensor analysis of fMRI data. KDD 2013: 194-202 - [c45]Ian Davidson, Buyue Qian, Xiang Wang, Jieping Ye:
Multi-objective Multi-view Spectral Clustering via Pareto Optimization. SDM 2013: 234-242 - [c44]Ian Davidson, Hongfei Li, Buyue Qian, Jun Wang, Xiang Wang:
Active Learning to Rank using Pairwise Supervision. SDM 2013: 297-305 - [i3]Ian Davidson:
Minimum Message Length Clustering Using Gibbs Sampling. CoRR abs/1301.3851 (2013) - 2012
- [j8]Ian N. Davidson, Sean Gilpin, Peter B. Walker:
Behavioral event data and their analysis. Data Min. Knowl. Discov. 25(3): 635-653 (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. ACM Trans. Knowl. Discov. Data 6(4): 18:1-18:26 (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]Peter B. Walker, Ian N. Davidson:
Exploring New Methodologies for the Analysis of Functional Magnetic Resonance Imaging (fMRI) Following Closed-Head Injuries. HCI (20) 2011: 120-128 - [c37]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 - [c36]Sean Gilpin, Ian N. Davidson:
Incorporating SAT solvers into hierarchical clustering algorithms: an efficient and flexible approach. KDD 2011: 1136-1144 - 2010
- [j6]Xiaoli Z. Fern, Ian Davidson, Jennifer G. Dy:
MultiClust 2010: discovering, summarizing and using multiple clusterings. SIGKDD Explor. 12(2): 47-49 (2010) - [c35]Buyue Qian, Ian Davidson:
Semi-Supervised Dimension Reduction for Multi-Label Classification. AAAI 2010: 569-574 - [c34]Xiang Wang, Ian Davidson:
Active Spectral Clustering. ICDM 2010: 561-568 - [c33]Xiang Wang, Ian Davidson:
Flexible constrained spectral clustering. KDD 2010: 563-572 - [c32]Mahmud 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 - [c31]Ian Davidson, S. S. Ravi, Leonid Shamis:
A SAT-based Framework for Efficient Constrained Clustering. SDM 2010: 94-105
2000 – 2009
- 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. Eur. J. Oper. Res. 197(2): 764-772 (2009) - [c30]Xiang Wang, Ian Davidson:
Discovering Contexts and Contextual Outliers Using Random Walks in Graphs. ICDM 2009: 1034-1039 - [c29]Ian Davidson:
Knowledge Driven Dimension Reduction for Clustering. IJCAI 2009: 1034-1039 - [c28]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
- [c27]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) - [c26]Ian Davidson, S. S. Ravi:
Intractability and clustering with constraints. ICML 2007: 201-208 - [c25]Ian Davidson, S. S. Ravi, Martin Ester:
Efficient incremental constrained clustering. KDD 2007: 240-249 - [c24]Rong Ge, Martin Ester, Wen Jin, Ian Davidson:
Constraint-driven clustering. KDD 2007: 320-329 - [c23]Wei Fan, Ian Davidson:
On Sample Selection Bias and Its Efficient Correction via Model Averaging and Unlabeled Examples. SDM 2007: 320-331 - 2006
- [c22]Ian Davidson, S. S. Ravi:
Identifying and Generating Easy Sets of Constraints for Clustering. AAAI 2006: 336-341 - [c21]Kiri Wagstaff, Sugato Basu, Ian Davidson:
When Is Constrained Clustering Beneficial, and Why?. AAAI 2006 - [c20]Kun Zhang, Wei Fan, Xiaojing Yuan, Ian Davidson, Xiangshang Li:
Forecasting Skewed Biased Stochastic Ozone Days: Analyses and Solutions. ICDM 2006: 753-764 - [c19]Wei Fan, Ian Davidson:
Reverse testing: an efficient framework to select amongst classifiers under sample selection bias. KDD 2006: 147-156 - [c18]Ian Davidson, Kiri Wagstaff
, Sugato Basu:
Measuring Constraint-Set Utility for Partitional Clustering Algorithms. PKDD 2006: 115-126 - [c17]Ian Davidson, Wei Fan:
When Efficient Model Averaging Out-Performs Boosting and Bagging. PKDD 2006: 478-486 - 2005
- [c16]Minoo Aminian, Ian Davidson:
Active Learning with Partially Labeled Data via Bias Reduction. FLAIRS 2005: 810-811 - [c15]Wei Fan, Ian Davidson, Bianca Zadrozny, Philip S. Yu:
An Improved Categorization of Classifier's Sensitivity on Sample Selection Bias. ICDM 2005: 605-608 - [c14]Ashwin Satyanarayana, Ian Davidson:
A Dynamic Adaptive Sampling Algorithm (DASA) for Real World Applications: Finger Print Recognition and Face Recognition. ISMIS 2005: 631-640 - [c13]Ian Davidson, S. S. Ravi:
Agglomerative Hierarchical Clustering with Constraints: Theoretical and Empirical Results. PKDD 2005: 59-70 - [c12]Ian Davidson, S. S. Ravi:
Clustering with Constraints: Feasibility Issues and the k-Means Algorithm. SDM 2005: 138-149 - 2004
- [c11]Ian Davidson:
An Ensemble Technique for Stable Learners with Performance Bounds. AAAI 2004: 330-335 - [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. AI&M 2004 - [c8]Ke Yin, Ian Davidson:
Bayesian Model Averaging Across Model Spaces via Compact Encoding. AI&M 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: 3-18 - 2000
- [c2]Ian Davidson:
Minimum Message Length Clustering Using Gibbs Sampling. UAI 2000: 160-167
1990 – 1999
- 1996
- [c1]Arkadi Kosmynin, Ian Davidson:
Using Background Contextual Knowledge for Document Representation. PODP 1996: 123-133
1980 – 1989
- 1985
- [j1]Ian Davidson:
Testing conformance to OSI standards. Comput. Commun. 8(4): 170-179 (1985)
Coauthor Index
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