1. Home ›
  2. Centers and Labs
    3. ›
  3. DIAL Publications

DIAL Publications

2019

  1. Daheng Wang, Tianwen Jiang, Nitesh V. Chawla, Meng Jiang. “TUBE: Embedding Behavior Outcomes for Predicting Success.” Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining PDF
  2. Chuxu Zhang, Dongjin Song, Chao Huang, Ananthram Swami, Nitesh V. Chawla. “Heterogeneous Graph Neural Network.” 25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) PDF
  3. Munira Syed, Jermaine Marshall, Aastha Nigam, Nitesh V. Chawla. “Gender Prediction Through Synthetic Resampling of User Profiles Using SeqGANs.” International Conference on Computational Data and Social Networks (CSoNet), 2019 PDF
  4. Munira Syed, Malolan Chetlur, Shazia Afzal, G. Alex Ambros, Nitesh V. Chawla. “Implicit and Explicit Emotions in MOOCs.” Educational Data Mining (EDM) PDF
  5. Munira Syed, Trunojoyo Anggara, Alison Lanski, Xiaojing Duan, G. Alex Ambrose, Nitesh V. Chawla. “Integrated Closed-loop Learning Analytics Scheme in a First Year Experience Course.” Learning Analytics and Knowledge (LAK) PDF
  6. Suwen Lin, Louis Faust, Pablo Robles-Granda, Tomasz Kajdanowicz, Nitesh V. Chawla. “Social Network Structure is Predictive of Health and Wellness.” PLOS ONE PDF
  7. Louis Faust, Keith Feldman, Nitesh V. Chawla. “Examining the Weekend Effect Across ICU Performance Metrics.” BMC Critical Care PDF
  8. Louis Faust, Priscilla Jiménez-Pazmino, James K. Holland, Omar Lizardo, David Hachen, Nitesh V. Chawla. “What 30 Days Tells Us About 3 Years: Identifying Early Signs of User Abandonment and Non-Adherence.” Proceedings of the 13th EAI International Conference on Pervasive Computing PDF
  9. Louis Faust, Cheng Wang, David Hachen, Omar Lizardo, Nitesh V. Chawla. “PATX: A Framework for Extracting Moderate-Vigorous Physical Activity Trends From Wearable Fitness Tracker Data.” JMIR mHealth and uHealth PDF
  10. Beenish Chaudhry, Louis Faust, Nitesh V. Chawla. “Development and Evaluation of a Web Application for Prenatal Care Coordinators in the United States.” International Conference on Design Science Research in Information Systems PDF
  11. Frederick Nwanganga, Nitesh V. Chawla, Gregory Madey. “Statistical Analysis and Modeling of Heterogeneous Workloads on Amazon’s Public Cloud Infrastructure.” Proceedings of the 52nd Hawaii International Conference on System Sciences PDF
  12. Aastha Nigam, Reid Johnson, Dong Wang, Nitesh V. Chawla. “Characterizing online health and wellness information consumption: A study.” Information Fusion PDF
  13. Jun Tao, Martin Imre, Chaoli Wang, Nitesh V. Chawla, Hanqi Guo, Gökhan Sever, Seung Hyun Kim . “Exploring Time-Varying Multivariate Volume Data Using Matrix of Isosurface Similarity Maps.” IEEE Transactions on Visualization and Computer Graphics PDF
  14. Chuxu Zhang, Ananthram Swami, Nitesh V. Chawla. “SHNE: Representation Learning for Semantic-Associated Heterogeneous Networks.” The 12th ACM International Conference on Web Search and Data Mining (WSDM 2019) PDF
  15. Chuxu Zhang, Dongjin Song, Yuncong Chen, Xinyang Feng, Cristian Lumezanu, Wei Cheng, Jingchao Ni, Bo Zong, Haifeng Chen, Nitesh V. Chawla. “A Deep Neural Network for Unsupervised Anomaly Detection and Diagnosis in Multivariate Time Series Data.” The 33rd Conference on Artificial Intelligence (AAAI 2019) PDF
  16. Xian Wu, Baoxu Shi, Yuxiao Dong, Chao Huang, Nitesh V. Chawla. “Neural Tensor Factorization for Temporal Interaction Learning.” The 12th ACM International Conference on Web Search and Data Mining (WSDM 2019)PDF

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
Pages: 1 2 3 4 5 6 7 8 9 10 11