1. Biran, O., & Cotton, C. (2017). Explanation and justification in machine learning: A survey. XAI workshop at IJCAI 2017, Melbourne, Australia. http://www.cs.columbia.edu/~orb/papers/xai_survey_paper_2017.pdf. Accessed June 25, 2018.
2. Biran, O., & McKeown, K. (2014). Justification narratives for individual classifications. AutoML workshop at ICML 2014, Beijing, China. http://www.cs.columbia.edu/~orb/papers/justification_automl_2014.pdf. Accessed June 21, 2018.
3. Biran, O., & McKeown, K. (2017). Human-centric justification of machine learning predictions. In: C. Sierra (Ed.), Proceedings of the twenty-sixth international joint conference on artificial intelligence. Main track (pp. 1461–1467). https://www.ijcai.org/proceedings/2017/0202.pdf. Accessed June 25, 2018.
4. Buduma, N. (2017). Fundamentals of deep learning: Designing next-generation machine intelligence algorithms. With contributions by Nicholas Locascio. Sebastopol, CA: O’Reilly Media, Inc.
5. Campbell, M., Hoane, A. J., & Hsu, F. (2002). Deep blue. Artificial Intelligence, 134, 57–83.