@inproceedings{871,
  author = {Yasitha Liyanage and Daphney-Stavroula Zois and Charalampos Chelmis},
  title = {On–The–Fly Feature Selection and Classification with Application to Civic Engagement Platforms},
  abstract = {Online feature selection and classification is crucial for time sensitive decision making. Existing work however either assumes that features are independent or produces a fixed number of features for classification. Instead, we propose an optimal framework to perform joint feature selection and classification on-the-fly while relaxing the assumption on feature independence. The effectiveness of the proposed approach is showed by classifying urban issue reports on the SeeClickFix civic engagement platform. A significant reduction in the average number of features used is observed without a drop in the classification accuracy.},
  year = {2020},
  journal = {2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
  chapter = {3762},
  pages = {5},
  month = {05},
  url = {https://par.nsf.gov/biblio/10196234},
  doi = {10.1109/ICASSP40776.2020.9053564},
}