Interpretability of Black Box Models Through Data-View Extraction and Shadow Model Creation

Rupam Patir, Shubham Singhal, C. Anantaram, Vikram Goyal. Interpretability of Black Box Models Through Data-View Extraction and Shadow Model Creation. In Haiqin Yang, Kitsuchart Pasupa, Andrew Chi-Sing Leung, James T. Kwok, Jonathan H. Chan, Irwin King, editors, Neural Information Processing - 27th International Conference, ICONIP 2020, Bangkok, Thailand, November 18-22, 2020, Proceedings, Part V. Volume 1333 of Communications in Computer and Information Science, pages 378-385, Springer, 2020. [doi]

@inproceedings{PatirSAG20,
  title = {Interpretability of Black Box Models Through Data-View Extraction and Shadow Model Creation},
  author = {Rupam Patir and Shubham Singhal and C. Anantaram and Vikram Goyal},
  year = {2020},
  doi = {10.1007/978-3-030-63823-8_44},
  url = {https://doi.org/10.1007/978-3-030-63823-8_44},
  researchr = {https://researchr.org/publication/PatirSAG20},
  cites = {0},
  citedby = {0},
  pages = {378-385},
  booktitle = {Neural Information Processing - 27th International Conference, ICONIP 2020, Bangkok, Thailand, November 18-22, 2020, Proceedings, Part V},
  editor = {Haiqin Yang and Kitsuchart Pasupa and Andrew Chi-Sing Leung and James T. Kwok and Jonathan H. Chan and Irwin King},
  volume = {1333},
  series = {Communications in Computer and Information Science},
  publisher = {Springer},
  isbn = {978-3-030-63823-8},
}