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Update README.rst #46

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ZhongLIFR Jul 4, 2024
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yzhao062 Jul 4, 2024
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Update README.rst 
Added two recent anomaly interpretability papers published in top journals
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ZhongLIFR committed Jul 4, 2024
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Expand Up @@ -354,6 +354,8 @@ Contextual outlier interpretation
Mining multidimensional contextual outliers from categorical relational data IDA 2015 [#Tang2015Mining]_ `[PDF] <http://www.cs.sfu.ca/~jpei/publications/Contextual%20outliers.pdf>`_
Discriminative features for identifying and interpreting outliers ICDE 2014 [#Dang2014Discriminative]_ `[PDF] <http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.706.5744&rep=rep1&type=pdf>`_
Sequential Feature Explanations for Anomaly Detection TKDD 2019 [#Siddiqui2019Sequential]_ `[HTML] <https://dl.acm.org/citation.cfm?id=3230666>`_
A Survey on Explainable Anomaly Detection TKDD 2023 [#Li2023XAD]_ `[HTML] <https://dl.acm.org/doi/10.1145/3609333>`_
Explainable Contextual Anomaly Detection Using Quantile Regression Forests DMKD 2023 [#Li2023QCAD]_ `[HTML] <https://link.springer.com/article/10.1007/s10618-023-00967-z>`_
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.. [#Li2019MAD] Li, D., Chen, D., Shi, L., Jin, B., Goh, J. and Ng, S.K., 2019. MAD-GAN: Multivariate Anomaly Detection for Time Series Data with Generative Adversarial Networks. arXiv preprint arXiv:1901.04997.

.. [#Li2023XAD] Li, Z., Zhu, Y. and Van Leeuwen, M., 2023. A survey on explainable anomaly detection. *ACM Transactions on Knowledge Discovery from Data*, 18(1), pp.1-54.

.. [#Li2023QCAD] Li, Z. and Van Leeuwen, M., 2023. Explainable contextual anomaly detection using quantile regression forests. *Data Mining and Knowledge Discovery*, 37(6), pp.2517-2563.

.. [#Liu2008Isolation] Liu, F.T., Ting, K.M. and Zhou, Z.H., 2008, December. Isolation forest. In *International Conference on Data Mining*\ , pp. 413-422. IEEE.

.. [#Liu2018Clustering] Liu, H., Li, J., Wu, Y. and Fu, Y., 2018. Clustering with Outlier Removal. arXiv preprint arXiv:1801.01899.
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