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AI Explainability 360: Impact and Design.

, , , , , , , , , , , , , , , , , , , и . AAAI, стр. 12651-12657. AAAI Press, (2022)

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Regina Amith-Borchart

Menachem Amitai

Samuel Amiteye

Menachem Amitai

Amit Singh

 

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Learning Global Transparent Models consistent with Local Contrastive Explanations., , , и . NeurIPS, (2020)Robust Pattern Recognition Scheme for Devanagari Script., , и . CIS (1), том 3801 из Lecture Notes in Computer Science, стр. 1021-1026. Springer, (2005)Empirical or Invariant Risk Minimization? A Sample Complexity Perspective., , , , и . ICLR, OpenReview.net, (2021)Learning Global Transparent Models from Local Contrastive Explanations., , , и . CoRR, (2020)A Formal Framework to Characterize Interpretability of Procedures., , , и . CoRR, (2017)Deciding Fast and Slow: The Role of Cognitive Biases in AI-assisted Decision-making., , , , , и . Proc. ACM Hum. Comput. Interact., 6 (CSCW1): 83:1-83:22 (2022)Classifier Invariant Approach to Learn from Positive-Unlabeled Data., и . ICDM, стр. 102-111. IEEE, (2020)Learning Maximum Lag for Grouped Graphical Granger Models.. ICDM Workshops, стр. 217-224. IEEE Computer Society, (2010)Atomist or Holist? A Diagnosis and Vision for More Productive Interdisciplinary AI Ethics Dialogue., , и . CoRR, (2022)Treatment Effect Estimation Using Invariant Risk Minimization., , , , , и . ICASSP, стр. 5005-5009. IEEE, (2021)