Publications on this site might not be up to date. For the latest publications, please visit the Google Scholar page of the lab director.
| 2024 | |
| [53] | Leveraging Local Structure for Improving Model Explanations: An Information Propagation Approach (), In Proceedings of the 33rd ACM International Conference on Information and Knowledge Management (CIKM), 2024. |
| [52] | Characterizing Online Criticism of Partisan News Media Using Weakly Supervised Learning (), In Proceedings of the International AAAI Conference on Web and Social Media (ICWSM), 2024. |
| [51] | Forecasting Political News Engagement on Social Media (), In Proceedings of the International AAAI Conference on Web and Social Media (ICWSM), 2024. |
| [50] | How Does Empowering Users with Greater System Control Affect News Filter Bubbles? (), In Proceedings of the International AAAI Conference on Web and Social Media (ICWSM), 2024. |
| 2023 | |
| [49] | IDGI: A Framework to Eliminate Explanation Noise from Integrated Gradients (), In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023. |
| [48] | Context-aware Feature Selection and Classification (), In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), 2023. |
| 2022 | |
| [47] | Ranking-Constrained Learning with Rationales for Text Classification (), In Findings of the Association for Computational Linguistics: ACL 2022, Association for Computational Linguistics, 2022. |
| [46] | Understanding and Combating Filter Bubbles in News Recommender Systems (), PhD thesis, Illinois Institute of Technology, 2022. |
| [45] | OrganoID: A versatile deep learning platform for tracking and analysis of single-organoid dynamics (), In PLOS Computational Biology, Public Library of Science, volume 18, 2022. |
| [44] | Reducing Cross-Topic Political Homogenization in Content-Based News Recommendation (), In Proceedings of the 16th ACM Conference on Recommender Systems, Association for Computing Machinery, 2022. |
| [43] | Leaders or Followers? A Temporal Analysis of Tweets from IRA Trolls (), In Proceedings of the International AAAI Conference on Web and Social Media, 2022. |
| 2021 | |
| [42] | Computer vision reveals hidden variables underlying NF-κB activation in single cells (), In Science Advances, volume 7, 2021. |
| [41] | The Interaction between Political Typology and Filter Bubbles in News Recommendation Algorithms (), In WWW '21: Proceedings of the Web Conference, 2021. |
| [40] | Relational Classification of Biological Cells in Microscopy Images (), In AAAI Conference on Artificial Intelligence, 2021. |
| 2019 | |
| [39] | Active Inference for Predictive Models of Spatio-Temporal Domains (), PhD thesis, Illinois Institute of Technology, 2019. |
| [38] | Disciplinary learning from an authentic engineering context (), In Journal of Pre-College Engineering Education Research (J-PEER), Purdue University Press, volume 9, 2019. |
| [37] | Hindsight Analysis of the Chicago Food Inspection Forecasting Model (), In Proceedings of AAAI FSS-19: Artificial Intelligence in Government and Public Sector, 2019. |
| 2018 | |
| [36] | Learning with rationales for document classification (), In Machine Learning, 2018. |
| 2017 | |
| [35] | Active Learning with Rich Feedback (), PhD thesis, Illinois Institute of Technology, 2017. |
| [34] | Evidence-based uncertainty sampling for active learning (), In Data Mining and Knowledge Discovery, volume 31, 2017. |
| [33] | Active learning: an empirical study of common baselines (), In Data Mining and Knowledge Discovery, volume 31, 2017. |
| [32] | Active inference for dynamic Bayesian networks with an application to tissue engineering (), In Knowledge and Information Systems, volume 50, 2017. |
| 2016 | |
| [31] | Anytime Active Learning (), PhD thesis, Illinois Institute of Technology, 2016. |
| [30] | Towards Learning with Feature-Based Explanations for Document Classification (), In IJCAI Workshop on BeyondLabeler - Human is More than a Labeler, 2016. |
| [29] | Active Learning with Rationales for Identifying Operationally Significant Anomalies in Aviation (), In Proceedings of European Conference on Machine Learning and Principles and Practice of Knowledge Discovery (ECML-PKDD), 2016. |
| [28] | Active Inference and Dynamic Gaussian Bayesian Networks for Battery Optimization in Wireless Sensor Networks (), In Proceedings of AAAI Workshop on Artificial Intelligence for Smart Grids and Smart Buildings, 2016. |
| 2015 | |
| [27] | Active Learning with Rationales for Text Classification (), In North American Chapter of the Association for Computational Linguistics – Human Language Technologies, 2015. |
| 2014 | |
| [26] | Anytime Active Learning (), In AAAI Conference on Artificial Intelligence, 2014. |
| [25] | Dynamic Bayesian Network Modeling of Vascularization in Engineered Tissues (), In Proceedings of the Eleventh UAI Bayesian Modeling Applications Workshop, 2014. |
| 2013 | |
| [24] | Most-Surely vs. Least-Surely Uncertain (), In Proceedings of International Conference on Data Mining (ICDM), 2013. |
| [23] | Towards Anytime Active Learning: Interrupting Experts to Reduce Annotation Costs (), In ACM SIGKDD Workshop on Interactive Data Exploration and Analytics (IDEA'13), 2013. |
| 2012 | |
| [22] | Active Query Selection for Learning Rankers (), In ACM SIGIR Conference on Research and Development in Information Retrieval, 2012. |
| [21] | Combining Active Learning and Dynamic Dimensionality Reduction (), In SIAM International Conference on Data Mining (SDM), 2012. |
| 2011 | |
| [20] | Active Inference for Retrieval in Camera Networks (), In Workshop on Person Oriented Vision, 2011. |
| [19] | Dynamic Processing Allocation in Video (), In IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Computer Society, volume 33, 2011. |
| [18] | Value of Information Lattice: Exploiting Probabilistic Independence for Effective Feature Subset Acquisition (), In Journal of Artificial Intelligence Research (JAIR), volume 41, 2011. |
| 2010 | |
| [17] | Cost-Sensitive Information Acquisition in Structured Domains (), PhD thesis, University of Maryland - College Park, 2010. |
| [16] | Collective Classification (), In Encyclopedia of Machine Learning, 2010. |
| [15] | Active Learning for Networked Data (), In Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010. |
| [14] | Active Inference for Collective Classification (), In Twenty-Fourth Conference on Artificial Intelligence (AAAI NECTAR Track), 2010. |
| 2009 | |
| [13] | Reflect and Correct: A Misclassification Prediction Approach to Active Inference (), In ACM Transactions on Knowledge Discovery from Data, volume 3, 2009. |
| [12] | Collective Classification for Text Classification (), Chapter in Text Mining: Classification, Clustering, and Applications (Mehran Sahami, Ashok Srivastava, eds.), Taylor and Francis Group, 2009. |
| [11] | Efficient Resource-constrained Retrospective Analysis of Long Video Sequences (), In NIPS Workshop on Adaptive Sensing, Active Learning and Experimental Design: Theory, Methods and Applications, 2009. |
| [10] | Link-based Active Learning (), In NIPS Workshop on Analyzing Networks and Learning with Graphs, 2009. |
| 2008 | |
| [9] | Collective Classification in Network Data (), In AI Magazine, volume 29, 2008. |
| [8] | Interactive Entity Resolution in Relational Data: A Visual Analytic Tool and Its Evaluation (), In IEEE Transactions on Visualization and Computer Graphics, volume 14, 2008. |
| [7] | Effective Label Acquisition for Collective Classification (), In ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2008. |
| 2007 | |
| [6] | VOILA: Efficient Feature-value Acquisition for Classification (), In AAAI '07: Proceedings of the 22nd National Conference on Artificial Intelligence, 2007. |
| [5] | Combining Collective Classification and Link Prediction (), In Workshop on Mining Graphs and Complex Structures at the IEEE International Conference on Data Mining (ICDM-2007), 2007. |
| 2006 | |
| [4] | D-Dupe: An Interactive Tool for Entity Resolution in Social Networks (), In Visual Analytics Science and Technology (VAST), 2006. |
| 2005 | |
| [3] | D-Dupe: An Interactive Tool for Entity Resolution in Social Networks (), In International Symposium on Graph Drawing (Patrick Healy, Nikola S. Nikolov, eds.), Springer, volume 3843, 2005. |
| [2] | Capital and Benefit in Social Networks (), In ACM SIGKDD Workshop on Link Analysis and Group Detection (LinkKDD), 2005. |
| [1] | Explaining Recommendations: Satisfaction vs. Promotion (), In Proceedings of Beyond Personalization 2005: A Workshop on the Next Stage of Recommender Systems Research at the 2005 International Conference on Intelligent User Interfaces, 2005. |