BibTeX records: Madeleine Schneider

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@inproceedings{DBLP:conf/bigdataconf/SchneiderAB21,
  author       = {Madeleine Schneider and
                  David Aspinall and
                  Nathaniel D. Bastian},
  editor       = {Yixin Chen and
                  Heiko Ludwig and
                  Yicheng Tu and
                  Usama M. Fayyad and
                  Xingquan Zhu and
                  Xiaohua Hu and
                  Suren Byna and
                  Xiong Liu and
                  Jianping Zhang and
                  Shirui Pan and
                  Vagelis Papalexakis and
                  Jianwu Wang and
                  Alfredo Cuzzocrea and
                  Carlos Ordonez},
  title        = {Evaluating Model Robustness to Adversarial Samples in Network Intrusion
                  Detection},
  booktitle    = {2021 {IEEE} International Conference on Big Data (Big Data), Orlando,
                  FL, USA, December 15-18, 2021},
  pages        = {3343--3352},
  publisher    = {{IEEE}},
  year         = {2021},
  url          = {https://doi.org/10.1109/BigData52589.2021.9671580},
  doi          = {10.1109/BIGDATA52589.2021.9671580},
  timestamp    = {Fri, 13 Jan 2023 17:06:49 +0100},
  biburl       = {https://dblp.org/rec/conf/bigdataconf/SchneiderAB21.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@inproceedings{DBLP:conf/aaaiss/SchneiderT19,
  author       = {Madeleine Schneider and
                  Robert Thomsons},
  editor       = {Takashi Kido and
                  Keiki Takadama},
  title        = {What Makes a Good Diagnosis: An Algorithm to Detect Biased Training
                  Data},
  booktitle    = {Proceedings of the Symposium Interpretable {AI} for Well-being: Understanding
                  Cognitive Bias and Social Embeddedness co-located with Association
                  for the Advancement of Artificial Intelligence 2019 Spring Symposium
                  (AAAI-Spring Symposium 2019), Stanford, CA, March 25-27, 2019},
  series       = {{CEUR} Workshop Proceedings},
  volume       = {2448},
  publisher    = {CEUR-WS.org},
  year         = {2019},
  timestamp    = {Fri, 10 Mar 2023 16:22:39 +0100},
  biburl       = {https://dblp.org/rec/conf/aaaiss/SchneiderT19.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@inproceedings{DBLP:conf/hotsos/AndrewsBJSSYMAM19,
  author       = {Daniel Andrews and
                  Jennifer Behn and
                  Danielle Jaksha and
                  Jinwon Seo and
                  Madeleine Schneider and
                  James Yoon and
                  Suzanne J. Matthews and
                  Rajeev Agrawal and
                  Alexander S. Mentis},
  editor       = {Xenofon D. Koutsoukos and
                  Alvaro A. C{\'{a}}rdenas and
                  Ehab Al{-}Shaer},
  title        = {Exploring RNNs for analyzing Zeek {HTTP} data},
  booktitle    = {Proceedings of the 6th Annual Symposium on Hot Topics in the Science
                  of Security, HotSoS 2019, Nashville, TN, USA, April 1-3, 2019},
  pages        = {18:1--18:2},
  publisher    = {{ACM}},
  year         = {2019},
  url          = {https://doi.org/10.1145/3314058.3317291},
  doi          = {10.1145/3314058.3317291},
  timestamp    = {Thu, 14 Oct 2021 01:00:00 +0200},
  biburl       = {https://dblp.org/rec/conf/hotsos/AndrewsBJSSYMAM19.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}