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ORCIDIan Davidson
Ian N. 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)
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Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
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Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
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Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
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OpenAlex data
Load additional information about publications from 
.
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last updated on 2024-11-07 21:33 CET by the dblp team
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