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Robust Machine Learning Algorithms and Systems for Detection and Mitigation of Adversarial Attacks and Anomalies Proceedings of a Workshop (2019) / Chapter Skim
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Appendix C: Workshop Statement of Task
Pages 65-65

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From page 65...
... The current state of machine-driven approaches such as machine learning and natural language processing that can be used to generate and evaluate analytic products from disparate structured and unstructured data types and to detect anomalies; 2. Approaches for ensuring that machine-generated products compare favorably with those of trained human analysts; 3.
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Key Terms

  • machine learning
  • adversarial manipulation
  • analytic products
  • input data
  • disparate structured

  • model uncertainty
  • products compare
  • influence analytical
  • unstructured data
  • evaluate analytic

  • exploiting weaknesses
  • data types
  • detect anomalies
  • establish confidence
  • natural language

  • compare favorably
  • confidence hierarchies
  • analytical products
  • expected research
  • trained human

  • following research
  • manage risk
  • human analysts
  • error propagation
  • research knowledge

  • scientific workforce
  • technical objectives
  • workshop proceedings
  • current state
  • key performance


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