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DIAL Publications

2018

  1. Aastha Nigam, Kijung Shin, Ashwin Bahulkar, Bryan Hooi, David Hachen, Boleslaw K. Szymanski, Christos Faloutsos, Nitesh V. Chawla. “ONE-M: Modeling the Co-evolution of Opinions and Network Connections.” Joint European Conference on Machine Learning and Knowledge Discovery in Databases 2018 PDF
  2. Shao-Yuan Li, Yuan Jiang, Nitesh V. Chawla, and Zhi-Hua Zhou. “Multi-Label Learning from Crowds.” IEEE Transactions on Knowledge and Data Engineering 2018 PDF
  3. Alberto Fernández, Salvador Garcia, Francisco Herrera, Nitesh V. Chawla. “SMOTE for Learning from Imbalanced Data: Progress and Challenges, Marking the 15-year Anniversary.” Journal of Artificial Intelligence Research 2018 PDF
  4. Saurabh Nagrecha, Nitesh V. Chawla. “Cambio Score: quantifying climate-change impacts for MSMEs in developing countries.” Private-sector action in adaptation: Perspectives on the role of micro, small and medium size enterprises 2018 PDF
  5. Pamela Bilo Thomas, Daniel H. Robertson, Nitesh V. Chawla. “Predicting onset of complications from diabetes: a graph based approach.” Applied Network Science PDF
  6. Daheng Wang, Meng Jiang, Qingkai Zeng, Zachary Eberhart, Nitesh V. Chawla. “Multi-Type Itemset Embedding for Learning Behavior Success.” Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery Data Mining PDF
  7. Daheng Wang, Meng Jiang, Xueying Wang, Tong Zhao, Qingkai Zeng, Nitesh V. Chawla. “A Project Showcase for Planning Research Work towards Publishable Success.” 24th ACM SIGKDD International Conference on Knowledge Discovery Data Mining Project Showcase Track PDF
  8. Chuxu Zhang, Lu Yu, Xiangliang Zhang, Nitesh V. Chawla. “TSR:Task-Guided and Semantic-Aware Ranking for Academic Author-Paper Correlation Inference.” International Joint Conference on Artificial Intelligence (IJCAI2018) PDF
  9. Chao Huang, Junbo Zhange, Yu Zheng, Nitesh V. Chawla. “DeepCrime: Attentive Hierarchical Recurrent Networks for Crime Prediction.” International Conference on Information and Knowledge Management (CIKM’2018) PDF
  10. Xian Wu, Baoxu Shi, Yuxiao Dong, Chao Huang, Louis Faust, Nitesh V. Chawla . “RESTFul: Resolution-Aware Forecasting of Behavioral Time Series Data.” International Conference on Information and Knowledge Management (CIKM’2018) PDF
  11. Louis Faust, David Hachen, Omar Lizardo, Nitesh V. Chawla. “Quantifying Subjective Well-Being Using Trends in Weekend Activity.” 2018 IEEE International Conference on Healthcare Informatics (ICHI) PDF
  12. Beenish Chaudhry, Louis Faust, Nitesh V. Chawla. “Towards an Integrated mHealth Platform for Community-based Maternity Health Workers in Low-Income Communities.” 12th EAI International Conference on Pervasive Computing Technologies for Healthcare (PervasiveHealth 2018). PDF
  13. Jenn Gonya, Tondi Harrison, Keith Feldman, Melanie Stein, Nitesh Chawla. “Nursing networks in the NICU and their association with maternal stress: A pilot study.” Journal of Nursing Management, 2018 PDF
  14. Jenn Gonya, Keith Feldman, Kristen Brown, Melanie Stein, Sarah Keim, Kelly Boone, Robert Rumpf, William Ray, Nitesh V. Chawla, Eric Butter. “Human interaction in the NICU and its association with outcomes on the Brief Infant-Toddler Social and Emotional Assessment (BITSEA).” Early Human Development, 2018 PDF
  15. Keith Feldman, Reid A Johnson, Nitesh V Chawla. “The State of Data In Healthcare: Path towards standardization.” Journal of Healthcare Informatics Research (JHIR) PDF
  16. Saurabh Nagrecha, Reid A Johnson, Nitesh V Chawla. “FraudBuster: Reducing Fraud in an Auto Insurance Market.” Big Data PDF
  17. Keith Feldman, Spyros Kotoulas, Nitesh V Chawla. “TIQS: Targeted Iterative Question Selection for Health Interventions.” Journal of Healthcare Informatics Research (JHIR) PDF
  18. Keith Feldman, Mayra Duarte, Waldo Mikels-Carrasco, Nitesh V Chawla. “Leveraging health and wellness platforms to understand childhood obesity: A usability pilot of FitSpace.” 2018 IEEE EMBS International Conference on Biomedical and Health Informatics (BHI) PDF
  19. Chuxu Zhang, Lu Yu, Xiangliang Zhang, Nitesh Chawla. “ImWalkMF: Joint Matrix Factorization and Implicit Walk Integrative Learning for Recommendation.” IEEE International Conference on Big Data (Big Data) 2018, 2018 PDF
  20. Xian Wu, Yuxiao dong, Jun Tao, Chao Huang, Nitesh Chawla. “Fake Review Detection via Modeling Temporal and Behavioral Patterns.” IEEE International Conference on Big Data (Big Data) 2018, 2018 PDF
  21. Xian Wu, Yuxiao dong, Baoxu Shi, Nitesh Chawla. “Who will Attend This Event Together? Event Attendance Prediction via Deep LSTM Network.” Proceedings of the 18th SIAM International Conference on Data Mining (SDM), 2018 PDFChuxu Zhang, Chao Huang, Lu Yu, Xiangliang Zhang, Nitesh Chawla. “Camel: Content-Aware and Meta-path Augmented Metric Learning for Author Identification .” Proceedings of the Web Conference (WWW), 2018 PDF

2017

  1. Jermaine Marshall, Arturo Argueta, Dong Wang. “A Neural Network Approach for Truth Discovery in Social Sensing.” IEEE 14th International Conference on Mobile Ad Hoc and Sensor Systems (MASS) 2017, 2017 PDF
  2. Saebi, Mandana, Jian Xu, Lance M. Kaplan, Bruno Ribeiro, and Nitesh V. Chawla. “Efficient Modeling of Higher-order Dependencies in Networks: From Algorithm to Application for Anomaly Detection.” ArXiv, (2017). PDF
  3. Huang, Hong, Yuxiao Dong, Jie Tang, Hongxia Yang, Nitesh V. Chawla, and Xiaoming Fu. “Will Triadic Closure Strengthen Ties in Social Networks?.” ACM Transactions on Knowledge Discovery from Data (TKDD), 12(3): 30., 2017. PDF
  4. Daheng Wang, Meng Jiang, Xueying Wang, Nitesh Chawla, Paul Brunts. “Multifaceted Event Analysis on Cross-Media Network Data.” 1st International Workshop On Heterogenous Networks Analysis and Mining (HeteroNAM), 2017. PDF
  5. Jun Tao, Chaoli Wang, Nitesh V. Chawla, Lei Shi, and Seung Hyun Kim. “Semantic Flow Graph: A Framework for Discovering Object Relationships in Flow Fields.” IEEE Transactions on Visualization and Computer Graphics, 2017. PDF
  6. Yuxiao Dong, Nitesh V. Chawla, Jie Tang, Yang Yang, Yang Yang. “User Modeling on Demographic Attributes in Big Mobile Social Networks.” ACM Transactions on Information Systems (TOIS), 35(4): 35, 2017. PDF
  7. Keith Feldman, Louis Faust, Xian Wu, Chao Huang, Nitesh V. Chawla. “Beyond Volume: The Impact of Complex Healthcare Data on the Machine Learning Pipeline.” Towards Integrative Machine Learning and Knowledge Extraction. Springer, Cham: 150-169., 2017. PDF arXiv
  8. Saurabh Nagrecha, Pamela Bilo Thomas, Keith Feldman, Nitesh V. Chawla. “Predicting Chronic Heart Failure Using Diagnoses Graphs.” International Cross-Domain Conference for Machine Learning and Knowledge Extraction (CD-MAKE). Springer, Cham, 2017. PDF
  9. Shazia Afzal, Bikram Sengupta, Munira Syed, Nitesh Chawla, G. Alex Ambrose and Malolan Chetlur. “The ABC of MOOCs: Affect and its Inter-play with Behaviour and Cognition.” Proceedings of the 7th Affective Computing and Intelligent Interaction (ACII), 2017. PDF
  10. Pingjie Tang, Jed Pitera, Dmitry Zubarev, Nitesh V. Chawla. “Heterogeneous Materials Information Network Construction and Relevance Search.” Proceedings of the 4th IEEE International Conference on Data Science and Advanced Analytics (DSAA) Best Paper Award, 2017. PDF
  11. Abstract
  12. Frederick Nwanganga, Mandana Saebi, Gregory Madey, Nitesh Chawla. “A Minimum-Cost Flow Model for Workload Optimization on Cloud Infrastructure.” Proceedings of the 10th International Conference on Cloud Computing (Cloud), 2017. arXiv
  13. Chuxu Zhang, Lu Yu, Xiangliang Zhang, Nitesh Chawla. “ImWalkMF: Joint Matrix Factorization and Implicit Walk Integrative Learning for Recommendation.” Proceedings of the IEEE International Conference on Big Data (Big Data), 2017.
  14. Xian Wu, Yuxiao dong, Jun Tao, Chao Huang, Nitesh Chawla. “Fake Review Detection via Modeling Temporal and Behavioral Patterns.” Proceedings of the IEEE International Conference on Big Data (Big Data), 2017.
  15. Shuo Wang, Jieyun Song, Yide Yang, Yining Zhang, Nitesh V. Chawla,, Jun Ma and Haijun Wang. “Interaction between obesity and the Hypoxia Inducible Factor 3 Alpha Subunit rs3826795 polymorphism in relation with plasma alanine aminotransferase.” BMC medical genetics 18(1): 80, 2017. PDF
  16. Xian Wu, Yuxiao dong, Chao Huang, Jian Xu, Nitesh Chawla. “UAPD: Predicting Urban Anomalies from Spatial-Temporal Data.” Proceedings of the European Conference on Machine Learning & Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), 2017. PDF
  17. Aastha Nigam, Henry K. Dambanemuya, Madhav Joshi, Nitesh Chawla. “Harvesting Social Signals to Inform Peace Processes Implementation and Monitoring.” Big data Journal, 5(4): 337-355, 2017. PDF
  18. Yuxiao Dong, Hao Ma, Zhihong Shen, and Kuansan Wang. “A Century of Science: Globalization of Scientific Collaborations, Citations, and Innovations.” Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2017. arXiv PDF
  19. Yuxiao Dong, Nitesh V. Chawla, and Ananthram Swami. “metapath2vec: Scalable Representation Learning for Heterogeneous Networks.” Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2017. PDF
  20. Yuxiao Dong, Reid A. Johnson, Jian Xu, and Nitesh V. Chawla. “Structural Diversity and Homophily: A Study Across More Than One Hundred Big Networks.” Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2017. arXiv PDF
  21. Alberto Fernández, Sara del Río, Nitesh V. Chawla, and Francisco Herrera. “An Insight into Imbalanced Big Data Classification: Outcomes and Challenges.” Complex & Intelligent Systems, 3(2):105–120, 2017. PDF
  22. Md Mursalin, Yuan Zhang, Yuehui Chen, and Nitesh V. Chawla. “Automated Epileptic Seizure Detection Using Improved Correlation-based Feature Selection with Random Forest Classifier.” Neurocomputing, 241:204–214, 2017. PDF
  23. Chao Huang, Dong Wang, and Nitesh V. Chawla. “Scalable Uncertainty-Aware Truth Discovery in Big Data Social Sensing Applications for Cyber-Physical Systems.” IEEE Transactions on Big Data (TBD), 2017. PDF
  24. Louis Faust, Rachael Purta, David Hachen, Aaron Striegel, Christian Poellabauer, Omar Lizardo, and Nitesh V. Chawla. “Exploring Compliance: Observations from a Large Scale Fitbit Study.” Proceedings of the 2nd International Workshop on Social Sensing (SocialSens), 2017. PDF
  25. Jun Tao, Jian Xu, Chaoli Wang, and Nitesh V. Chawla. “HoNVis: Visualizing and Exploring Higher-Order Networks.” Proceedings of the 10th IEEE Pacific Visualization Symposium (PacificVis), 2017. arXiv PDF
  26. Saurabh Nagrecha, John Z. Dillon, and Nitesh V. Chawla. “MOOC Dropout Prediction: Lessons Learned from Making Pipelines Interpretable.” Proceedings of the 26th International Conference on World Wide Web Companion, 2017. PDF
  27. Pablo González, Jorge Díez, Nitesh V. Chawla, and Juan José del Coz. “Why is Quantification an Interesting Learning Problem?.” Progress in Artificial Intelligence (PRAI), 6(1):53–58, 2017. PDF
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