Testing conformance to OSI standards. - Ian Davidson (Comput. Commun., 1985)

Using Background Contextual Knowledge for Document Representation. - Arkadi Kosmynin; Ian Davidson (PODP, 1996)

Minimum Message Length Clustering Using Gibbs Sampling. - Ian Davidson (UAI, 2000)

Visualizing Clustering Results. - Ian Davidson (SDM, 2002)

Searching for Hidden Messages: Automatic Detection of Steganography. - George Berg; Ian Davidson; Ming-Yuan Duan; Goutam Paul 001 (IAAI, 2003)

An Ensemble Technique for Stable Learners with Performance Bounds. - Ian Davidson (AAAI, 2004)

An Information Theoretic Optimal Classifier for Semi-supervised Learning. - Ke Yin; Ian Davidson (IDEAL, 2004)

Using the Central Limit Theorem for Belief Network Learning. - Ian Davidson; Minoo Aminian (AI&M, 2004)

Bayesian Model Averaging Across Model Spaces via Compact Encoding. - Ke Yin; Ian Davidson (AI&M, 2004)

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

Locating secret messages in images. - Ian Davidson; Goutam Paul 001 (KDD, 2004)

Further Applications of a Particle Visualization Framework. - Ke Yin; Ian Davidson (PAKDD, 2004)

Active Learning with Partially Labeled Data via Bias Reduction. - Minoo Aminian; Ian Davidson (FLAIRS, 2005)

An Improved Categorization of Classifier's Sensitivity on Sample Selection Bias. - Wei Fan 001; Ian Davidson; Bianca Zadrozny; Philip S. Yu (ICDM, 2005)

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

Agglomerative Hierarchical Clustering with Constraints: Theoretical and Empirical Results. - Ian Davidson; S. S. Ravi (PKDD, 2005)

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

Identifying and Generating Easy Sets of Constraints for Clustering. - Ian Davidson; S. S. Ravi (AAAI, 2006)

When Is Constrained Clustering Beneficial, and Why?. - Kiri Wagstaff; Sugato Basu; Ian Davidson (AAAI, 2006)

Forecasting Skewed Biased Stochastic Ozone Days: Analyses and Solutions. - Kun Zhang 012; Wei Fan 001; Xiaojing Yuan; Ian Davidson; Xiangshang Li (ICDM, 2006)

Reverse testing: an efficient framework to select amongst classifiers under sample selection bias. - Wei Fan 001; Ian Davidson (KDD, 2006)

When Efficient Model Averaging Out-Performs Boosting and Bagging. - Ian Davidson; Wei Fan 001 (PKDD, 2006)

Measuring Constraint-Set Utility for Partitional Clustering Algorithms. - Ian Davidson; Kiri Wagstaff; Sugato Basu (PKDD, 2006)

Intractability and clustering with constraints. - Ian Davidson; S. S. Ravi (ICML, 2007)

Efficient incremental constrained clustering. - Ian Davidson; S. S. Ravi; Martin Ester (KDD, 2007)

Constraint-driven clustering. - Rong Ge 002; Martin Ester; Wen Jin; Ian Davidson (KDD, 2007)

On Sample Selection Bias and Its Efficient Correction via Model Averaging and Unlabeled Examples. - Wei Fan 001; Ian Davidson (SDM, 2007)

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

Editorial: Special issue on mining low-quality data. - Xingquan Zhu 001; Taghi M. Khoshgoftaar; Ian Davidson; Shichao Zhang 001 (Knowl. Inf. Syst., 2007)

Finding Alternative Clusterings Using Constraints. - Ian Davidson; Zijie Qi (ICDM, 2008)

Discovering Contexts and Contextual Outliers Using Random Walks in Graphs. - Xiang Wang 001; Ian Davidson (ICDM, 2009)

Knowledge Driven Dimension Reduction for Clustering. - Ian Davidson (IJCAI, 2009)

A principled and flexible framework for finding alternative clusterings. - Zijie Qi; Ian Davidson (KDD, 2009)

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

Data preparation using data quality matrices for classification mining. - Ian Davidson; Giri Kumar Tayi (Eur. J. Oper. Res., 2009)

Clustering with Constraints. - Ian Davidson (Encyclopedia of Database Systems, 2009)

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

Active Spectral Clustering. - Xiang Wang 001; Ian Davidson (ICDM, 2010)

Unifying dependent clustering and disparate clustering for non-homogeneous data. - Mahmud Shahriar Hossain; Satish Tadepalli; Layne T. Watson; Ian Davidson; Richard F. Helm; Naren Ramakrishnan (KDD, 2010)

Flexible constrained spectral clustering. - Xiang Wang 001; Ian Davidson (KDD, 2010)

A SAT-based Framework for Efficient Constrained Clustering. - Ian Davidson; S. S. Ravi; Leonid Shamis (SDM, 2010)

MultiClust 2010: discovering, summarizing and using multiple clusterings. - Xiaoli Z. Fern; Ian Davidson; Jennifer G. Dy (SIGKDD Explor., 2010)

Exploring New Methodologies for the Analysis of Functional Magnetic Resonance Imaging (fMRI) Following Closed-Head Injuries. - Peter B. Walker; Ian N. Davidson (HCI (20), 2011)

Multi-source domain adaptation and its application to early detection of fatigue. - Rita Chattopadhyay; Jieping Ye; Sethuraman Panchanathan; Wei Fan 001; Ian Davidson (KDD, 2011)

Incorporating SAT solvers into hierarchical clustering algorithms: an efficient and flexible approach. - Sean Gilpin; Ian N. Davidson (KDD, 2011)

Improving document clustering using automated machine translation. - Xiang Wang 001; Buyue Qian; Ian Davidson (CIKM, 2012)

Labels vs. Pairwise Constraints: A Unified View of Label Propagation and Constrained Spectral Clustering. - Xiang Wang 001; Buyue Qian; Ian Davidson (ICDM, 2012)

Keyless Steganography in Spatial Domain Using Energetic Pixels. - Goutam Paul 001; Ian Davidson; Imon Mukherjee; S. S. Ravi (ICISS, 2012)

Two approaches to understanding when constraints help clustering. - Ian Davidson (KDD, 2012)

A Reconstruction Error Formulation for Semi-Supervised Multi-task and Multi-view Learning - Buyue Qian; Xiang Wang 001; Ian Davidson (CoRR, 2012)

Behavioral event data and their analysis. - Ian N. Davidson; Sean Gilpin; Peter B. Walker (Data Min. Knowl. Discov., 2012)

Multisource domain adaptation and its application to early detection of fatigue. - Rita Chattopadhyay; Qian Sun 002; Wei Fan 001; Ian Davidson; Sethuraman Panchanathan; Jieping Ye (ACM Trans. Knowl. Discov. Data, 2012)

Formalizing Hierarchical Clustering as Integer Linear Programming. - Sean Gilpin; Siegfried Nijssen; Ian N. Davidson (AAAI, 2013)

Clustering with Complex Constraints - Algorithms and Applications. - Weifeng Zhi; Xiang Wang 001; Buyue Qian; Patrick Butler; Naren Ramakrishnan; Ian Davidson (AAAI, 2013)

Efficient hierarchical clustering of large high dimensional datasets. - Sean Gilpin; Buyue Qian; Ian Davidson (CIKM, 2013)

Guided Learning Algorithms: An Application of Constrained Spectral Partitioning to Functional Magnetic Resonance Imaging (fMRI). - Henry L. Phillips; Peter B. Walker; Carrie H. Kennedy; Owen T. Carmichael; Ian N. Davidson (HCI (24), 2013)

Active Matrix Completion. - Shayok Chakraborty; Jiayu Zhou; Vineeth Nallure Balasubramanian; Sethuraman Panchanathan; Ian Davidson; Jieping Ye (ICDM, 2013)

Fast Pairwise Query Selection for Large-Scale Active Learning to Rank. - Buyue Qian; Xiang Wang 001; Jun Wang 006; Hongfei Li; Nan Cao 001; Weifeng Zhi; Ian Davidson (ICDM, 2013)

Joint Transfer and Batch-mode Active Learning. - Rita Chattopadhyay; Wei Fan 001; Ian Davidson; Sethuraman Panchanathan; Jieping Ye (ICML (3), 2013)

Active Learning from Relative Queries. - Buyue Qian; Xiang Wang 001; Fei Wang 001; Hongfei Li; Jieping Ye; Ian Davidson (IJCAI, 2013)

Network discovery via constrained tensor analysis of fMRI data. - Ian N. Davidson; Sean Gilpin; Owen T. Carmichael; Peter B. Walker (KDD, 2013)

Guided learning for role discovery (GLRD): framework, algorithms, and applications. - Sean Gilpin; Tina Eliassi-Rad; Ian N. Davidson (KDD, 2013)

Active Learning to Rank using Pairwise Supervision. - Ian Davidson; Hongfei Li; Buyue Qian; Jun Wang 006; Xiang Wang 001 (SDM, 2013)

Multi-objective Multi-view Spectral Clustering via Pareto Optimization. - Ian Davidson; Buyue Qian; Xiang Wang 001; Jieping Ye (SDM, 2013)

How to "alternatize" a clustering algorithm. - Mahmud Shahriar Hossain; Naren Ramakrishnan; Ian Davidson; Layne T. Watson (Data Min. Knowl. Discov., 2013)

Batch Mode Active Sampling Based on Marginal Probability Distribution Matching. - Rita Chattopadhyay; Zheng Wang 011; Wei Fan 001; Ian Davidson; Sethuraman Panchanathan; Jieping Ye (ACM Trans. Knowl. Discov. Data, 2013)

A Flexible Framework for Projecting Heterogeneous Data. - Aubrey Gress; Ian Davidson (CIKM, 2014)

Spectral Clustering for Medical Imaging. - Chia-Tung Kuo; Peter B. Walker; Owen T. Carmichael; Ian Davidson (ICDM, 2014)

Clinical risk prediction with multilinear sparse logistic regression. - Fei Wang 001; Ping Zhang 016; Buyue Qian; Xiang Wang 001; Ian Davidson (KDD, 2014)

Directed Interpretable Discovery in Tensors with Sparse Projection. - Chia-Tung Kuo; Ian Davidson (SDM, 2014)

Self-Taught Spectral Clustering via Constraint Augmentation. - Xiang Wang 001; Jun Wang 006; Buyue Qian; Fei Wang 001; Ian Davidson (SDM, 2014)

Stochastic Coordinate Coding and Its Application for Drosophila Gene Expression Pattern Annotation. - Binbin Lin; Qingyang Li 001; Qian Sun 002; Ming-Jun Lai; Ian Davidson; Wei Fan 001; Jieping Ye (CoRR, 2014)

On constrained spectral clustering and its applications. - Xiang Wang 001; Buyue Qian; Ian Davidson (Data Min. Knowl. Discov., 2014)

Learning Multiple Relative Attributes With Humans in the Loop. - Buyue Qian; Xiang Wang 001; Nan Cao 001; Yu-Gang Jiang 001; Ian Davidson (IEEE Trans. Image Process., 2014)

Propagating Ranking Functions on a Graph: Algorithms and Applications. - Buyue Qian; Xiang Wang 001; Ian Davidson (AAAI, 2015)

Constrained Tensor Decomposition via Guidance: Increased Inter and Intra-Group Reliability in fMRI Analyses. - Peter B. Walker; Sean Gilpin; Sidney G. Fooshee; Ian Davidson (HCI (15), 2015)

Accurate Estimation of Generalization Performance for Active Learning. - Aubrey Gress; Ian Davidson (ICDM, 2015)

Unified and Contrasting Cuts in Multiple Graphs: Application to Medical Imaging Segmentation. - Chia-Tung Kuo; Xiang Wang 001; Peter B. Walker; Owen T. Carmichael; Jieping Ye; Ian Davidson (KDD, 2015)

Structural Graphical Lasso for Learning Mouse Brain Connectivity. - Sen Yang 004; Qian Sun 002; Shuiwang Ji; Peter Wonka; Ian Davidson; Jieping Ye (KDD, 2015)

Learning Automated Agents from Historical Game Data via Tensor Decomposition. - Peter B. Walker; Ian Davidson (SBP, 2015)

Complex Interactions in Social and Event Network Analysis. - Peter B. Walker; Sidney G. Fooshee; Ian Davidson (SBP, 2015)

A Framework for Simplifying Trip Data into Networks via Coupled Matrix Factorization. - Chia-Tung Kuo; James Bailey 001; Ian Davidson (SDM, 2015)

Guest editorial: Special issue on data mining for medicine and healthcare. - Fei Wang 001; Gregor Stiglic; Zoran Obradovic; Ian Davidson (Data Min. Knowl. Discov., 2015)

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. - Yan Sun; Ian Davidson (Inf. Comput. Secur., 2015)

A Reconstruction Error Based Framework for Multi-Label and Multi-View Learning. - Buyue Qian; Xiang Wang 001; Jieping Ye; Ian Davidson (IEEE Trans. Knowl. Data Eng., 2015)

A Framework for Outlier Description Using Constraint Programming. - Chia-Tung Kuo; Ian Davidson (AAAI, 2016)

A Framework for Actionable Clustering Using Constraint Programming. - Thi-Bich-Hanh Dao; Christel Vrain; Khanh-Chuong Duong; Ian Davidson (ECAI, 2016)

Probabilistic Formulations of Regression with Mixed Guidance. - Aubrey Gress; Ian Davidson (ICDM, 2016)

Scalable Fast Rank-1 Dictionary Learning for fMRI Big Data Analysis. - Xiang Li 001; Milad Makkie; Binbin Lin; Mojtaba Sedigh Fazli; Ian Davidson; Jieping Ye; Tianming Liu 001; Shannon Quinn (KDD, 2016)

Accelerating Online CP Decompositions for Higher Order Tensors. - Shuo Zhou 001; Xuan Vinh Nguyen; James Bailey 001; Yunzhe Jia; Ian Davidson (KDD, 2016)

Some Advances in Role Discovery in Graphs. - Sean Gilpin; Chia-Tung Kuo; Tina Eliassi-Rad; Ian Davidson (CoRR, 2016)

A Framework for Minimal Clustering Modification via Constraint Programming. - Chia-Tung Kuo; S. S. Ravi; Thi-Bich-Hanh Dao; Christel Vrain; Ian Davidson (AAAI, 2017)

Transfer Learning in Intelligent Tutoring Systems - Results, Challenges and New Directions. - Aubrey Gress; Jeremiah T. Folsom-Kovarik; Ian Davidson (FLAIRS, 2017)

Knowledge Guided Short-Text Classification for Healthcare Applications. - Shilei Cao 001; Buyue Qian; Changchang Yin; Xiaoyu Li 007; Jishang Wei; Qinghua Zheng; Ian Davidson (ICDM, 2017)

Deep Similarity-Based Batch Mode Active Learning with Exploration-Exploitation. - Changchang Yin; Buyue Qian; Shilei Cao 001; Xiaoyu Li 007; Jishang Wei; Qinghua Zheng; Ian Davidson (ICDM, 2017)

Recurrent Encoder-Decoder Networks for Time-Varying Dense Prediction. - Tao Zeng; Bian Wu; Jiayu Zhou; Ian Davidson; Shuiwang Ji (ICDM, 2017)

Scalable Constrained Spectral Clustering via the Randomized Projected Power Method. - Weifeng Zhi; Buyue Qian; Ian Davidson (ICDM, 2017)

Unsupervised Network Discovery for Brain Imaging Data. - Zilong Bai; Peter B. Walker; Anna E. Tschiffely; Fei Wang 001; Ian Davidson (KDD, 2017)

A flexible ILP formulation for hierarchical clustering. - Sean Gilpin; Ian Davidson (Artif. Intell., 2017)

Dense Transformer Networks. - Jun Li 098; Yongjun Chen; Lei Cai; Ian Davidson; Shuiwang Ji (CoRR, 2017)

Transfer Regression via Pairwise Similarity Regularization. - Aubrey Gress; Ian Davidson (CoRR, 2017)

Keyless dynamic optimal multi-bit image steganography using energetic pixels. - Goutam Paul 001; Ian Davidson; Imon Mukherjee; S. S. Ravi (Multim. Tools Appl., 2017)

Applications of Transductive Spectral Clustering Methods in a Military Medical Concussion Database. - Peter B. Walker; Jacob N. Norris; Anna E. Tschiffely; Melissa L. Mehalick; Craig A. Cunningham; Ian N. Davidson (IEEE ACM Trans. Comput. Biol. Bioinform., 2017)

Human Guided Linear Regression With Feature-Level Constraints. - Aubrey Gress; Ian Davidson (AAAI, 2018)

Extreme Learning to Rank via Low Rank Assumption. - Minhao Cheng; Ian Davidson; Cho-Jui Hsieh (ICML, 2018)

Descriptive Clustering: ILP and CP Formulations with Applications. - Thi-Bich-Hanh Dao; Chia-Tung Kuo; S. S. Ravi; Christel Vrain; Ian Davidson (IJCAI, 2018)

Discovering Models from Structural and Behavioral Brain Imaging Data. - Zilong Bai; Buyue Qian; Ian Davidson (KDD, 2018)

The Cluster Description Problem - Complexity Results, Formulations and Approximations. - Ian Davidson; Antoine Gourru; S. S. Ravi (NeurIPS, 2018)

Mixtures of Block Models for Brain Networks. - Zilong Bai; Peter B. Walker; Ian Davidson (SDM, 2018)

Image Constrained Blockmodelling: A Constraint Programming Approach. - Mohadeseh Ganji; Jeffrey Chan; Peter J. Stuckey; James Bailey 001; Christopher Leckie; Kotagiri Ramamohanarao; Ian Davidson (SDM, 2018)

On The Equivalence of Tries and Dendrograms - Efficient Hierarchical Clustering of Traffic Data. - Chia-Tung Kuo; Ian Davidson (CoRR, 2018)

Clustering with Constraints. - Ian Davidson (Encyclopedia of Database Systems (2nd ed.), 2018)

Towards Fluid Machine Intelligence: Can We Make a Gifted AI? - Ian Davidson; Peter B. Walker (AAAI, 2019)

Dense Transformer Networks for Brain Electron Microscopy Image Segmentation. - Jun Li 098; Yongjun Chen; Lei Cai; Ian Davidson; Shuiwang Ji (IJCAI, 2019)

A Framework for Deep Constrained Clustering - Algorithms and Advances. - Hongjing Zhang; Sugato Basu; Ian Davidson (ECML/PKDD (1), 2019)

Approaches to Enhancing Transfer of Training using Adaptive Instructional Systems. - Jeremiah T. Folsom-Kovarik; Behrooz Mostafavi; Robert A. Sottilare; Ian Davidson; Ray Perez; Peter B. Walker (SoftCOM, 2019)

Towards Fair Deep Clustering With Multi-State Protected Variables. - Bokun Wang; Ian Davidson (CoRR, 2019)

Deep Constrained Clustering - Algorithms and Advances. - Hongjing Zhang; Sugato Basu; Ian Davidson (CoRR, 2019)

Coverage-based Outlier Explanation. - Yue Wu; Leman Akoglu; Ian Davidson (CoRR, 2019)

Making Existing Clusterings Fairer: Algorithms, Complexity Results and Insights. - Ian Davidson; S. S. Ravi (AAAI, 2020)

Constraint Programming for an Efficient and Flexible Block Modeling Solver. - Alex Lucía Mattenet; Ian Davidson; Siegfried Nijssen; Pierre Schaus (AAAI, 2020)

Efficient Algorithms for Generating Provably Near-Optimal Cluster Descriptors for Explainability. - Prathyush Sambaturu; Aparna Gupta; Ian Davidson; S. S. Ravi; Anil Vullikanti; Andrew Warren (AAAI, 2020)

Constrained Clustering via Post-processing. - Nguyen-Viet-Dung Nghiem; Christel Vrain; Thi-Bich-Hanh Dao; Ian Davidson (DS, 2020)

A Framework for Determining the Fairness of Outlier Detection. - Ian Davidson; S. S. Ravi (ECAI, 2020)

Post-traitement pour la classification probabiliste non supervisée sous contraintes. - Nguyen-Viet-Dung Nghiem; Christel Vrain; Thi-Bich-Hanh Dao; Ian Davidson (EGC, 2020)

Block Model Guided Unsupervised Feature Selection. - Zilong Bai; Hoa Nguyen; Ian Davidson (KDD, 2020)

INPREM: An Interpretable and Trustworthy Predictive Model for Healthcare. - Xianli Zhang; Buyue Qian; Shilei Cao 001; Yang Li 139; Hang Chen; Yefeng Zheng 001; Ian Davidson (KDD, 2020)

Towards Description of Block Model on Graph. - Zilong Bai; S. S. Ravi; Ian Davidson (ECML/PKDD (3), 2020)

A Graph-Based Approach for Active Learning in Regression. - Hongjing Zhang; S. S. Ravi; Ian Davidson (SDM, 2020)

Behavioral differences: insights, explanations and comparisons of French and US Twitter usage during elections. - Ian Davidson; Antoine Gourru; Julien Velcin; Yue Wu (Soc. Netw. Anal. Min., 2020)

Towards Fair Deep Anomaly Detection. - Hongjing Zhang; Ian Davidson (FAccT, 2021)

Deep Descriptive Clustering. - Hongjing Zhang; Ian Davidson (IJCAI, 2021)

Fairness and Explanation in Clustering and Outlier Detection. - Ian Davidson (KDD, 2021)

Deep Fair Discriminative Clustering. - Hongjing Zhang; Ian Davidson (CoRR, 2021)

A framework for deep constrained clustering. - Hongjing Zhang; Tianyang Zhan; Sugato Basu; Ian Davidson (Data Min. Knowl. Discov., 2021)

Generic Constraint-based Block Modeling using Constraint Programming. - Alex Mattenet; Ian Davidson; Siegfried Nijssen; Pierre Schaus (J. Artif. Intell. Res., 2021)

A Self-Supervised Deep Learning Framework for Unsupervised Few-Shot Learning and Clustering. - Hongjing Zhang; Tianyang Zhan; Ian Davidson (Pattern Recognit. Lett., 2021)

Deep Learning for Prognosis Using Task-fMRI: A Novel Architecture and Training Scheme. - Ge Shi 007; Jason Smucny; Ian Davidson (KDD, 2022)

Explainable Clustering via Exemplars: Complexity and Efficient Approximation Algorithms. - Ian Davidson; Michael J. Livanos; Antoine Gourru; Peter B. Walker; Julien Velcin; S. S. Ravi (CoRR, 2022)

Towards Auditing Unsupervised Learning Algorithms and Human Processes For Fairness. - Ian Davidson; S. S. Ravi (CoRR, 2022)

Scalable Spectral Clustering with Group Fairness Constraints. - Ji Wang; Ding Lu; Ian Davidson; Zhaojun Bai (AISTATS, 2023)

Making clusterings fairer by post-processing: algorithms, complexity results and experiments. - Ian Davidson; Zilong Bai; Cindy Mylinh Tran; S. S. Ravi (Data Min. Knowl. Discov., 2023)

Context-Aware and Time-Aware Attention-Based Model for Disease Risk Prediction With Interpretability. - Xianli Zhang; Buyue Qian; Yang Li 139; Shilei Cao 001; Ian Davidson (IEEE Trans. Knowl. Data Eng., 2023)

Cooperative Knowledge Distillation: A Learner Agnostic Approach. - Michael J. Livanos; Ian Davidson; Stephen Wong (AAAI, 2024)

Foundations for Unfairness in Anomaly Detection - Case Studies in Facial Imaging Data. - Michael J. Livanos; Ian Davidson (AIES (1), 2024)

An Exemplars-Based Approach for Explainable Clustering: Complexity and Efficient Approximation Algorithms. - Ian Davidson; Michael J. Livanos; Antoine Gourru; Peter B. Walker; Julien Velcin; S. S. Ravi (SDM, 2024)

Identification and Uses of Deep Learning Backbones via Pattern Mining. - Michael J. Livanos; Ian Davidson (SDM, 2024)

ChaosMining: A Benchmark to Evaluate Post-Hoc Local Attribution Methods in Low SNR Environments. - Ge Shi 007; Ziwen Kan; Jason Smucny; Ian Davidson (CoRR, 2024)

Searching for Unfairness in Algorithms' Outputs: Novel Tests and Insights. - Ian Davidson; S. S. Ravi (AAAI, 2025)

CXAD: Contrastive Explanations for Anomaly Detection: Algorithms, Complexity Results and Experiments. - Ian Davidson; Nicolás Kennedy; S. S. Ravi (Trans. Mach. Learn. Res., 2025)

Using Graph Convolutional Networks to Address fMRI Small Data Problems. - Thomas Screven; Andras Necz; Jason Smucny; Ian Davidson (CoRR, 2025)