DIAL Publications

2021

  1. Yijun Tian, Chuxu Zhang, Ronald Metoyer, Nitesh Chawla. “Recipe Representation Learning with Networks.” 30th ACM International Conference on Information and Knowledge Management (CIKM) PDF
  2. Discriminative Entity-Aware Language Model for Virtual Assistants.” Interspeech 2021Best student paper nominee PDF
  3. Zhaojun Wang, Mandana Saebi, James J Corbett, Erin K Grey, Salvatore R Curasi. “Integrated Biological Risk and Cost Model Analysis Supports a Geopolitical Shift in Ballast Water Management.” Environmental Science & Technology PDF
  4. Zhaojun Wang, Amanda M. Countryman, James J. Corbett, Mandana Saebi, Nitesh V. Chawla. “Economic and environmental impacts of ballast water management on Small Island Developing States and Least Developed Countries.” Journal of Environmental Management arXiv
  5. Daheng Wang, Zhihan Zhang, Yihong Ma, Tong Zhao, Tianwen Jiang, Nitesh V. Chawla, Meng Jiang . “Modeling Co-evolution of Attributed and Structural Information in Graph Sequence.” PDF
  6. Daheng Wang, Qingkai Zeng, Nitesh V. Chawla, Meng Jiang . “Modeling Complementarity in Behavior Data with Multi-Type Itemset Embedding.” PDF

2020

  1. Zhichun Guo, Wenhau Yu, Chuxu Zhang, Meng Jiang, Nitesh V. Chawla. “GraSeq: Graph and Sequence Fusion Learning for Molecular Property Prediction.” Proceedings of the 29th ACM International Conference on Information and Knowledge Management 2020 (CIKM’ 2020) PDF
  2. Steven J. Krieg, Daniel H. Robertson, Meeta P. Pradhan, Nitesh V. Chawla. “Higher-order Networks of Diabetes Comorbidities: Disease Trajectories that Matter.” 2020 IEEE International Conference on Healthcare Informatics (ICHI) PDF
  3. Steven J. Krieg, Peter M. Kogge, Nitesh V. Chawla. “GrowHON: A Scalable Algorithm for Growing Higher-order Networks of Sequences.” 2020 International Conference on Complex Networks and Their Applications PDF
  4. Jennifer J. Schnur, Ryan Karl, Angélica García-Martinez, Meng Jiang, Nitesh V. Chawla. “Imputing Growth Snapshot Similarity in Early Childhood Development: A Tensor Decomposition Approach.” 2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) PDF
  5. Mandana Saebi, Jian Xu, Salvatore R. Curasi, Erin K. Grey, Nitesh V. Chawla, David M. Lodge. “Network analysis of ballast-mediated species transfer reveals important introduction and dispersal patterns in the Arctic.” Scientific Reports PDF
  6. Mandana Saebi, Giovanni Luca Ciampaglia, Lance M. Kaplan, Nitesh V. Chawla. “HONEM: Learning Embedding for Higher Order Networks.” Big Data arXiv
  7. 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.” EPJ Data Science 9, no. 1 (2020): 1-22. PDF
  8. Saebi, Mandana, Jian Xu, Erin K. Grey, David M. Lodge, James J. Corbett, and Nitesh Chawla.”Higher-order Patterns of Aquatic Species Spread through the Global Shipping Network.” PLOS ONE15, no. 7 (2020): e0220353. PDF
  9. Daheng Wang, Meng Jiang, Munira Syed, Oliver Conway, Vishal Juneja, Sriram Subramanian, Nitesh V. Chawla.”Calendar Graph Neural Networks for Modeling Time Structures in Spatiotemporal User Behaviors”. Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2020. PDF
  10. Wang, Daheng, Zhihan Zhang, Yihong Ma, Tong Zhao, Tianwen Jiang, Nitesh V. Chawla, and Meng Jiang. 2020. “Learning Attribute-Structure Co-Evolutions in Dynamic Graphs.” ArXiv. Republished from The Second International Workshop on Deep Learning on Graphs: Methods and Applications (DLG-KDD’20), Best Paper Award of DLG-KDD’20. PDF
  11. Steven J. Krieg, Jennifer J. Schnur, Jermaine D. Marshall, Matthew M. Schoenbauer, and Nitesh V. Chawla. Pandemic Pulse: Unraveling and Modeling Social Signals During the COVID-19 Pandemic. Digital Government 2, no. 2. 2020: 9 pages. PDF
  12. Jian Xu, Mandana Saebi, Bruno Ribeiro, Lance M. Kaplan, Nitesh V. Chawla. “Detecting Anomalies in Sequential Data with Higher-order Networks.” PDF