Ian Davidson - RankMe

160 papers A* 60A 23B 2C 3Misc 4Journal 50Unranked 16

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	CXAD: Contrastive Explanations for Anomaly Detection: Algorithms, Complexity Results and Experiments. Trans. Mach. Learn. Res. Ian Davidson, Nicolás Kennedy, S. S. Ravi
2025	A*	`conf`	Searching for Unfairness in Algorithms' Outputs: Novel Tests and Insights. AAAI Ian Davidson, S. S. Ravi
2025	J	`jnl`	Using Graph Convolutional Networks to Address fMRI Small Data Problems. CoRR Thomas Screven, Andras Necz, Jason Smucny, Ian Davidson
2024	A	`conf`	An Exemplars-Based Approach for Explainable Clustering: Complexity and Efficient Approximation Algorithms. SDM Ian Davidson, Michael J. Livanos, Antoine Gourru, Peter B. Walker, Julien Velcin, S. S. Ravi
2024	J	`jnl`	ChaosMining: A Benchmark to Evaluate Post-Hoc Local Attribution Methods in Low SNR Environments. CoRR Ge Shi, Ziwen Kan, Jason Smucny, Ian Davidson
2024	A*	`conf`	Cooperative Knowledge Distillation: A Learner Agnostic Approach. AAAI Michael J. Livanos, Ian Davidson, Stephen Wong
2024	J	`jnl`	Cooperative Knowledge Distillation: A Learner Agnostic Approach. CoRR Michael J. Livanos, Ian Davidson, Stephen Wong
2024	—	`conf`	Foundations for Unfairness in Anomaly Detection - Case Studies in Facial Imaging Data. AIES (1) Michael J. Livanos, Ian Davidson
2024	J	`jnl`	Foundations for Unfairness in Anomaly Detection - Case Studies in Facial Imaging Data. CoRR Michael J. Livanos, Ian Davidson
2024	A	`conf`	Identification and Uses of Deep Learning Backbones via Pattern Mining. SDM Michael J. Livanos, Ian Davidson
2024	J	`jnl`	Identification and Uses of Deep Learning Backbones via Pattern Mining. CoRR Michael J. Livanos, Ian Davidson
2023	J	`jnl`	Context-Aware and Time-Aware Attention-Based Model for Disease Risk Prediction With Interpretability. IEEE Trans. Knowl. Data Eng. Xianli Zhang, Buyue Qian, Yang Li, Shilei Cao, Ian Davidson
2023	J	`jnl`	Making clusterings fairer by post-processing: algorithms, complexity results and experiments. Data Min. Knowl. Discov. Ian Davidson, Zilong Bai, Cindy Mylinh Tran, S. S. Ravi
2023	A	`conf`	Scalable Spectral Clustering with Group Fairness Constraints. AISTATS Ji Wang, Ding Lu, Ian Davidson, Zhaojun Bai
2022	A*	`conf`	Deep Learning for Prognosis Using Task-fMRI: A Novel Architecture and Training Scheme. KDD Ge Shi, Jason Smucny, Ian Davidson
2022	J	`jnl`	Explainable Clustering via Exemplars: Complexity and Efficient Approximation Algorithms. CoRR Ian Davidson, Michael J. Livanos, Antoine Gourru, Peter B. Walker, Julien Velcin, S. S. Ravi
2022	J	`jnl`	Scalable Spectral Clustering with Group Fairness Constraints. CoRR Ji Wang, Ding Lu, Zhaojun Bai, Ian Davidson
2022	J	`jnl`	Towards Auditing Unsupervised Learning Algorithms and Human Processes For Fairness. CoRR Ian Davidson, S. S. Ravi
2021	J	`jnl`	A Framework for Deep Constrained Clustering. CoRR Hongjing Zhang, Tianyang Zhan, Sugato Basu, Ian Davidson
2021	J	`jnl`	A Self-Supervised Deep Learning Framework for Unsupervised Few-Shot Learning and Clustering. Pattern Recognit. Lett. Hongjing Zhang, Tianyang Zhan, Ian Davidson
2021	J	`jnl`	A framework for deep constrained clustering. Data Min. Knowl. Discov. Hongjing Zhang, Tianyang Zhan, Sugato Basu, Ian Davidson
2021	A*	`conf`	Deep Descriptive Clustering. IJCAI Hongjing Zhang, Ian Davidson
2021	J	`jnl`	Deep Descriptive Clustering. CoRR Hongjing Zhang, Ian Davidson
2021	J	`jnl`	Deep Fair Discriminative Clustering. CoRR Hongjing Zhang, Ian Davidson
2021	A*	`conf`	Fairness and Explanation in Clustering and Outlier Detection. KDD Ian Davidson
2021	J	`jnl`	Generic Constraint-based Block Modeling using Constraint Programming. J. Artif. Intell. Res. Alex Mattenet, Ian Davidson, Siegfried Nijssen, Pierre Schaus
2021	A	`ed.`	Proceedings of the 2021 SIAM International Conference on Data Mining, SDM 2021, Virtual Event, April 29 - May 1, 2021. SDM Carlotta Demeniconi, Ian Davidson
2021	—	`conf`	Towards Fair Deep Anomaly Detection. FAccT Hongjing Zhang, Ian Davidson
2020	A	`conf`	A Framework for Determining the Fairness of Outlier Detection. ECAI Ian Davidson, S. S. Ravi
2020	A	`conf`	A Graph-Based Approach for Active Learning in Regression. SDM Hongjing Zhang, S. S. Ravi, Ian Davidson
2020	J	`jnl`	A Graph-Based Approach for Active Learning in Regression. CoRR Hongjing Zhang, S. S. Ravi, Ian Davidson
2020	J	`jnl`	Behavioral differences: insights, explanations and comparisons of French and US Twitter usage during elections. Soc. Netw. Anal. Min. Ian Davidson, Antoine Gourru, Julien Velcin, Yue Wu
2020	A*	`conf`	Block Model Guided Unsupervised Feature Selection. KDD Zilong Bai, Hoa Nguyen, Ian Davidson
2020	J	`jnl`	Block Model Guided Unsupervised Feature Selection. CoRR Zilong Bai, Hoa Nguyen, Ian Davidson
2020	B	`conf`	Constrained Clustering via Post-processing. DS Nguyen-Viet-Dung Nghiem, Christel Vrain, Thi-Bich-Hanh Dao, Ian Davidson
2020	A*	`conf`	Constraint Programming for an Efficient and Flexible Block Modeling Solver. AAAI Alex Lucía Mattenet, Ian Davidson, Siegfried Nijssen, Pierre Schaus
2020	A*	`conf`	Efficient Algorithms for Generating Provably Near-Optimal Cluster Descriptors for Explainability. AAAI Prathyush Sambaturu, Aparna Gupta, Ian Davidson, S. S. Ravi, Anil Vullikanti, Andrew Warren
2020	J	`jnl`	Efficient Algorithms for Generating Provably Near-Optimal Cluster Descriptors for Explainability. CoRR Prathyush Sambaturu, Aparna Gupta, Ian Davidson, S. S. Ravi, Anil Vullikanti, Andrew Warren
2020	A*	`conf`	INPREM: An Interpretable and Trustworthy Predictive Model for Healthcare. KDD Xianli Zhang, Buyue Qian, Shilei Cao, Yang Li, Hang Chen, Yefeng Zheng, Ian Davidson
2020	A*	`conf`	Making Existing Clusterings Fairer: Algorithms, Complexity Results and Insights. AAAI Ian Davidson, S. S. Ravi
2020	—	`conf`	Post-traitement pour la classification probabiliste non supervisée sous contraintes. EGC Nguyen-Viet-Dung Nghiem, Christel Vrain, Thi-Bich-Hanh Dao, Ian Davidson
2020	—	`conf`	Towards Description of Block Model on Graph. ECML/PKDD (3) Zilong Bai, S. S. Ravi, Ian Davidson
2020	J	`jnl`	Towards Fair Deep Anomaly Detection. CoRR Hongjing Zhang, Ian Davidson
2019	—	`conf`	A Framework for Deep Constrained Clustering - Algorithms and Advances. ECML/PKDD (1) Hongjing Zhang, Sugato Basu, Ian Davidson
2019	Misc	`conf`	Approaches to Enhancing Transfer of Training using Adaptive Instructional Systems. SoftCOM Jeremiah T. Folsom-Kovarik, Behrooz Mostafavi, Robert A. Sottilare, Ian Davidson, Ray Perez, Peter B. Walker
2019	J	`jnl`	Coverage-based Outlier Explanation. CoRR Yue Wu, Leman Akoglu, Ian Davidson
2019	J	`jnl`	Deep Constrained Clustering - Algorithms and Advances. CoRR Hongjing Zhang, Sugato Basu, Ian Davidson
2019	A*	`conf`	Dense Transformer Networks for Brain Electron Microscopy Image Segmentation. IJCAI Jun Li, Yongjun Chen, Lei Cai, Ian Davidson, Shuiwang Ji
2019	—	`conf`	Generic Constraint-Based Block Modeling Using Constraint Programming. BNAIC/BENELEARN Alex Mattenet, Ian Davidson, Siegfried Nijssen, Pierre Schaus
2019	A	`conf`	Generic Constraint-Based Block Modeling Using Constraint Programming. CP Alex Mattenet, Ian Davidson, Siegfried Nijssen, Pierre Schaus
2019	J	`jnl`	Towards Fair Deep Clustering With Multi-State Protected Variables. CoRR Bokun Wang, Ian Davidson
2019	A*	`conf`	Towards Fluid Machine Intelligence: Can We Make a Gifted AI? AAAI Ian Davidson, Peter B. Walker
2018	—	`ch.`	Clustering with Constraints. Encyclopedia of Database Systems (2nd ed.) Ian Davidson
2018	A*	`conf`	Descriptive Clustering: ILP and CP Formulations with Applications. IJCAI Thi-Bich-Hanh Dao, Chia-Tung Kuo, S. S. Ravi, Christel Vrain, Ian Davidson
2018	A*	`conf`	Discovering Models from Structural and Behavioral Brain Imaging Data. KDD Zilong Bai, Buyue Qian, Ian Davidson
2018	A*	`conf`	Extreme Learning to Rank via Low Rank Assumption. ICML Minhao Cheng, Ian Davidson, Cho-Jui Hsieh
2018	A*	`conf`	Human Guided Linear Regression With Feature-Level Constraints. AAAI Aubrey Gress, Ian Davidson
2018	A	`conf`	Image Constrained Blockmodelling: A Constraint Programming Approach. SDM Mohadeseh Ganji, Jeffrey Chan, Peter J. Stuckey, James Bailey, Christopher Leckie, Kotagiri Ramamohanarao, Ian Davidson
2018	A	`conf`	Mixtures of Block Models for Brain Networks. SDM Zilong Bai, Peter B. Walker, Ian Davidson
2018	J	`jnl`	On The Equivalence of Tries and Dendrograms - Efficient Hierarchical Clustering of Traffic Data. CoRR Chia-Tung Kuo, Ian Davidson
2018	J	`jnl`	Probabilistic Formulations of Regression with Mixed Guidance. CoRR Aubrey Gress, Ian Davidson
2018	A*	`conf`	The Cluster Description Problem - Complexity Results, Formulations and Approximations. NeurIPS Ian Davidson, Antoine Gourru, S. S. Ravi
2017	A*	`conf`	A Framework for Minimal Clustering Modification via Constraint Programming. AAAI Chia-Tung Kuo, S. S. Ravi, Thi-Bich-Hanh Dao, Christel Vrain, Ian Davidson
2017	J	`jnl`	A flexible ILP formulation for hierarchical clustering. Artif. Intell. Sean Gilpin, Ian Davidson
2017	A*	`conf`	Deep Similarity-Based Batch Mode Active Learning with Exploration-Exploitation. ICDM Changchang Yin, Buyue Qian, Shilei Cao, Xiaoyu Li, Jishang Wei, Qinghua Zheng, Ian Davidson
2017	J	`jnl`	Dense Transformer Networks. CoRR Jun Li, Yongjun Chen, Lei Cai, Ian Davidson, Shuiwang Ji
2017	J	`jnl`	Keyless dynamic optimal multi-bit image steganography using energetic pixels. Multim. Tools Appl. Goutam Paul, Ian Davidson, Imon Mukherjee, S. S. Ravi
2017	A*	`conf`	Knowledge Guided Short-Text Classification for Healthcare Applications. ICDM Shilei Cao, Buyue Qian, Changchang Yin, Xiaoyu Li, Jishang Wei, Qinghua Zheng, Ian Davidson
2017	A*	`conf`	Recurrent Encoder-Decoder Networks for Time-Varying Dense Prediction. ICDM Tao Zeng, Bian Wu, Jiayu Zhou, Ian Davidson, Shuiwang Ji
2017	A*	`conf`	Scalable Constrained Spectral Clustering via the Randomized Projected Power Method. ICDM Weifeng Zhi, Buyue Qian, Ian Davidson
2017	Misc	`conf`	Transfer Learning in Intelligent Tutoring Systems - Results, Challenges and New Directions. FLAIRS Aubrey Gress, Jeremiah T. Folsom-Kovarik, Ian Davidson
2017	J	`jnl`	Transfer Regression via Pairwise Similarity Regularization. CoRR Aubrey Gress, Ian Davidson
2017	A*	`conf`	Unsupervised Network Discovery for Brain Imaging Data. KDD Zilong Bai, Peter B. Walker, Anna E. Tschiffely, Fei Wang, Ian Davidson
2016	A	`conf`	A Framework for Actionable Clustering Using Constraint Programming. ECAI Thi-Bich-Hanh Dao, Christel Vrain, Khanh-Chuong Duong, Ian Davidson
2016	A*	`conf`	A Framework for Outlier Description Using Constraint Programming. AAAI Chia-Tung Kuo, Ian Davidson
2016	A*	`conf`	Accelerating Online CP Decompositions for Higher Order Tensors. KDD Shuo Zhou, Xuan Vinh Nguyen, James Bailey, Yunzhe Jia, Ian Davidson
2016	A*	`conf`	Probabilistic Formulations of Regression with Mixed Guidance. ICDM Aubrey Gress, Ian Davidson
2016	A*	`conf`	Scalable Fast Rank-1 Dictionary Learning for fMRI Big Data Analysis. KDD Xiang Li, Milad Makkie, Binbin Lin, Mojtaba Sedigh Fazli, Ian Davidson, Jieping Ye, Tianming Liu, Shannon Quinn
2016	J	`jnl`	Some Advances in Role Discovery in Graphs. CoRR Sean Gilpin, Chia-Tung Kuo, Tina Eliassi-Rad, Ian Davidson
2015	A	`conf`	A Framework for Simplifying Trip Data into Networks via Coupled Matrix Factorization. SDM Chia-Tung Kuo, James Bailey, Ian Davidson
2015	J	`jnl`	A Reconstruction Error Based Framework for Multi-Label and Multi-View Learning. IEEE Trans. Knowl. Data Eng. Buyue Qian, Xiang Wang, Jieping Ye, Ian Davidson
2015	A*	`conf`	Accurate Estimation of Generalization Performance for Active Learning. ICDM Aubrey Gress, Ian Davidson
2015	—	`conf`	Complex Interactions in Social and Event Network Analysis. SBP Peter B. Walker, Sidney G. Fooshee, Ian Davidson
2015	—	`conf`	Constrained Tensor Decomposition via Guidance: Increased Inter and Intra-Group Reliability in fMRI Analyses. HCI (15) Peter B. Walker, Sean Gilpin, Sidney G. Fooshee, Ian Davidson
2015	J	`jnl`	Guest editorial: Special issue on data mining for medicine and healthcare. Data Min. Knowl. Discov. Fei Wang, Gregor Stiglic, Zoran Obradovic, Ian Davidson
2015	J	`jnl`	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. Yan Sun, Ian Davidson
2015	—	`conf`	Learning Automated Agents from Historical Game Data via Tensor Decomposition. SBP Peter B. Walker, Ian Davidson
2015	A*	`conf`	Propagating Ranking Functions on a Graph: Algorithms and Applications. AAAI Buyue Qian, Xiang Wang, Ian Davidson
2015	A*	`conf`	Structural Graphical Lasso for Learning Mouse Brain Connectivity. KDD Sen Yang, Qian Sun, Shuiwang Ji, Peter Wonka, Ian Davidson, Jieping Ye
2015	A*	`conf`	Unified and Contrasting Cuts in Multiple Graphs: Application to Medical Imaging Segmentation. KDD Chia-Tung Kuo, Xiang Wang, Peter B. Walker, Owen T. Carmichael, Jieping Ye, Ian Davidson
2014	A	`conf`	A Flexible Framework for Projecting Heterogeneous Data. CIKM Aubrey Gress, Ian Davidson
2014	A*	`conf`	Clinical risk prediction with multilinear sparse logistic regression. KDD Fei Wang, Ping Zhang, Buyue Qian, Xiang Wang, Ian Davidson
2014	A	`conf`	Directed Interpretable Discovery in Tensors with Sparse Projection. SDM Chia-Tung Kuo, Ian Davidson
2014	J	`jnl`	Learning Multiple Relative Attributes With Humans in the Loop. IEEE Trans. Image Process. Buyue Qian, Xiang Wang, Nan Cao, Yu-Gang Jiang, Ian Davidson
2014	J	`jnl`	On constrained spectral clustering and its applications. Data Min. Knowl. Discov. Xiang Wang, Buyue Qian, Ian Davidson
2014	A	`conf`	Self-Taught Spectral Clustering via Constraint Augmentation. SDM Xiang Wang, Jun Wang, Buyue Qian, Fei Wang, Ian Davidson
2014	A*	`conf`	Spectral Clustering for Medical Imaging. ICDM Chia-Tung Kuo, Peter B. Walker, Owen T. Carmichael, Ian Davidson
2014	J	`jnl`	Stochastic Coordinate Coding and Its Application for Drosophila Gene Expression Pattern Annotation. CoRR Binbin Lin, Qingyang Li, Qian Sun, Ming-Jun Lai, Ian Davidson, Wei Fan, Jieping Ye
2013	A*	`conf`	Active Learning from Relative Queries. IJCAI Buyue Qian, Xiang Wang, Fei Wang, Hongfei Li, Jieping Ye, Ian Davidson
2013	A	`conf`	Active Learning to Rank using Pairwise Supervision. SDM Ian Davidson, Hongfei Li, Buyue Qian, Jun Wang, Xiang Wang
2013	A*	`conf`	Active Matrix Completion. ICDM Shayok Chakraborty, Jiayu Zhou, Vineeth Nallure Balasubramanian, Sethuraman Panchanathan, Ian Davidson, Jieping Ye
2013	J	`jnl`	Batch Mode Active Sampling Based on Marginal Probability Distribution Matching. ACM Trans. Knowl. Discov. Data Rita Chattopadhyay, Zheng Wang, Wei Fan, Ian Davidson, Sethuraman Panchanathan, Jieping Ye
2013	A*	`conf`	Clustering with Complex Constraints - Algorithms and Applications. AAAI Weifeng Zhi, Xiang Wang, Buyue Qian, Patrick Butler, Naren Ramakrishnan, Ian Davidson
2013	A	`conf`	Efficient hierarchical clustering of large high dimensional datasets. CIKM Sean Gilpin, Buyue Qian, Ian Davidson
2013	A*	`conf`	Fast Pairwise Query Selection for Large-Scale Active Learning to Rank. ICDM Buyue Qian, Xiang Wang, Jun Wang, Hongfei Li, Nan Cao, Weifeng Zhi, Ian Davidson
2013	J	`jnl`	How to "alternatize" a clustering algorithm. Data Min. Knowl. Discov. Mahmud Shahriar Hossain, Naren Ramakrishnan, Ian Davidson, Layne T. Watson
2013	—	`conf`	Joint Transfer and Batch-mode Active Learning. ICML (3) Rita Chattopadhyay, Wei Fan, Ian Davidson, Sethuraman Panchanathan, Jieping Ye
2013	J	`jnl`	Minimum Message Length Clustering Using Gibbs Sampling CoRR Ian Davidson
2013	A	`conf`	Multi-objective Multi-view Spectral Clustering via Pareto Optimization. SDM Ian Davidson, Buyue Qian, Xiang Wang, Jieping Ye
2012	J	`jnl`	A Reconstruction Error Formulation for Semi-Supervised Multi-task and Multi-view Learning CoRR Buyue Qian, Xiang Wang, Ian Davidson
2012	A*	`conf`	Batch mode active sampling based on marginal probability distribution matching. KDD Rita Chattopadhyay, Zheng Wang, Wei Fan, Ian Davidson, Sethuraman Panchanathan, Jieping Ye
2012	A	`conf`	Improving document clustering using automated machine translation. CIKM Xiang Wang, Buyue Qian, Ian Davidson
2012	Misc	`conf`	Keyless Steganography in Spatial Domain Using ICISS Goutam Paul, Ian Davidson, Imon Mukherjee, S. S. Ravi
2012	A*	`conf`	Labels vs. Pairwise Constraints: A Unified View of Label Propagation and Constrained Spectral Clustering. ICDM Xiang Wang, Buyue Qian, Ian Davidson
2012	J	`jnl`	Multisource domain adaptation and its application to early detection of fatigue. ACM Trans. Knowl. Discov. Data Rita Chattopadhyay, Qian Sun, Wei Fan, Ian Davidson, Sethuraman Panchanathan, Jieping Ye
2012	J	`jnl`	On Constrained Spectral Clustering and Its Applications CoRR Xiang Wang, Buyue Qian, Ian Davidson
2012	A*	`conf`	Two approaches to understanding when constraints help clustering. KDD Ian Davidson
2011	A*	`conf`	Multi-source domain adaptation and its application to early detection of fatigue. KDD Rita Chattopadhyay, Jieping Ye, Sethuraman Panchanathan, Wei Fan, Ian Davidson
2010	A	`conf`	A SAT-based Framework for Efficient Constrained Clustering. SDM Ian Davidson, S. S. Ravi, Leonid Shamis
2010	A*	`conf`	Active Spectral Clustering. ICDM Xiang Wang, Ian Davidson
2010	A*	`conf`	Flexible constrained spectral clustering. KDD Xiang Wang, Ian Davidson
2010	J	`jnl`	MultiClust 2010: discovering, summarizing and using multiple clusterings. SIGKDD Explor. Xiaoli Z. Fern, Ian Davidson, Jennifer G. Dy
2010	A*	`conf`	Semi-Supervised Dimension Reduction for Multi-Label Classification. AAAI Buyue Qian, Ian Davidson
2010	A*	`conf`	Unifying dependent clustering and disparate clustering for non-homogeneous data. KDD Mahmud Shahriar Hossain, Satish Tadepalli, Layne T. Watson, Ian Davidson, Richard F. Helm, Naren Ramakrishnan
2009	A*	`conf`	A principled and flexible framework for finding alternative clusterings. KDD Zijie Qi, Ian Davidson
2009	—	`ch.`	Clustering with Constraints. Encyclopedia of Database Systems Ian Davidson
2009	J	`jnl`	Data preparation using data quality matrices for classification mining. Eur. J. Oper. Res. Ian Davidson, Giri Kumar Tayi
2009	A*	`conf`	Discovering Contexts and Contextual Outliers Using Random Walks in Graphs. ICDM Xiang Wang, Ian Davidson
2009	A*	`conf`	Knowledge Driven Dimension Reduction for Clustering. IJCAI Ian Davidson
2009	J	`jnl`	Using instance-level constraints in agglomerative hierarchical clustering: theoretical and empirical results. Data Min. Knowl. Discov. Ian Davidson, S. S. Ravi
2008	A*	`conf`	Finding Alternative Clusterings Using Constraints. ICDM Ian Davidson, Zijie Qi
2007	A*	`conf`	Constraint-driven clustering. KDD Rong Ge, Martin Ester, Wen Jin, Ian Davidson
2007	J	`jnl`	Editorial: Special issue on mining low-quality data. Knowl. Inf. Syst. Xingquan Zhu, Taghi M. Khoshgoftaar, Ian Davidson, Shichao Zhang
2007	A*	`conf`	Efficient incremental constrained clustering. KDD Ian Davidson, S. S. Ravi, Martin Ester
2007	A*	`conf`	Intractability and clustering with constraints. ICML Ian Davidson, S. S. Ravi
2007	A	`conf`	On Sample Selection Bias and Its Efficient Correction via Model Averaging and Unlabeled Examples. SDM Wei Fan, Ian Davidson
2007	J	`jnl`	The complexity of non-hierarchical clustering with instance and cluster level constraints. Data Min. Knowl. Discov. Ian Davidson, S. S. Ravi
2006	A*	`conf`	Forecasting Skewed Biased Stochastic Ozone Days: Analyses and Solutions. ICDM Kun Zhang, Wei Fan, Xiaojing Yuan, Ian Davidson, Xiangshang Li
2006	A*	`conf`	Identifying and Generating Easy Sets of Constraints for Clustering. AAAI Ian Davidson, S. S. Ravi
2006	—	`conf`	Measuring Constraint-Set Utility for Partitional Clustering Algorithms. PKDD Ian Davidson, Kiri Wagstaff, Sugato Basu
2006	A*	`conf`	Reverse testing: an efficient framework to select amongst classifiers under sample selection bias. KDD Wei Fan, Ian Davidson
2006	—	`conf`	When Efficient Model Averaging Out-Performs Boosting and Bagging. PKDD Ian Davidson, Wei Fan
2006	A*	`conf`	When Is Constrained Clustering Beneficial, and Why?. AAAI Kiri Wagstaff, Sugato Basu, Ian Davidson
2005	C	`conf`	A Dynamic Adaptive Sampling Algorithm (DASA) for Real World Applications: Finger Print Recognition and Face Recognition. ISMIS Ashwin Satyanarayana, Ian Davidson
2005	Misc	`conf`	Active Learning with Partially Labeled Data via Bias Reduction. FLAIRS Minoo Aminian, Ian Davidson
2005	—	`conf`	Agglomerative Hierarchical Clustering with Constraints: Theoretical and Empirical Results. PKDD Ian Davidson, S. S. Ravi
2005	A*	`conf`	An Improved Categorization of Classifier's Sensitivity on Sample Selection Bias. ICDM Wei Fan, Ian Davidson, Bianca Zadrozny, Philip S. Yu
2005	A	`conf`	Clustering with Constraints: Feasibility Issues and the k-Means Algorithm. SDM Ian Davidson, S. S. Ravi
2004	A*	`conf`	A general approach to incorporate data quality matrices into data mining algorithms. KDD Ian Davidson, Ashish Grover, Ashwin Satyanarayana, Giri Kumar Tayi
2004	A*	`conf`	An Ensemble Technique for Stable Learners with Performance Bounds. AAAI Ian Davidson
2004	C	`conf`	An Information Theoretic Optimal Classifier for Semi-supervised Learning. IDEAL Ke Yin, Ian Davidson
2004	—	`conf`	Bayesian Model Averaging Across Model Spaces via Compact Encoding. AI&M Ke Yin, Ian Davidson
2004	B	`conf`	Further Applications of a Particle Visualization Framework. PAKDD Ke Yin, Ian Davidson
2004	A*	`conf`	Locating secret messages in images. KDD Ian Davidson, Goutam Paul
2004	—	`conf`	Using the Central Limit Theorem for Belief Network Learning. AI&M Ian Davidson, Minoo Aminian
2003	C	`conf`	Searching for Hidden Messages: Automatic Detection of Steganography. IAAI George Berg, Ian Davidson, Ming-Yuan Duan, Goutam Paul
2002	A	`conf`	Visualizing Clustering Results. SDM Ian Davidson
2000	A	`conf`	Minimum Message Length Clustering Using Gibbs Sampling. UAI Ian Davidson
1996	—	`conf`	Using Background Contextual Knowledge for Document Representation. PODP Arkadi Kosmynin, Ian Davidson
1985	J	`jnl`	Testing conformance to OSI standards. Comput. Commun. Ian Davidson