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Learning Global Transparent Models from Local Contrastive Explanations., , , and . CoRR, (2020)A Formal Framework to Characterize Interpretability of Procedures., , , and . CoRR, (2017)Deciding Fast and Slow: The Role of Cognitive Biases in AI-assisted Decision-making., , , , , and . Proc. ACM Hum. Comput. Interact., 6 (CSCW1): 83:1-83:22 (2022)Classifier Invariant Approach to Learn from Positive-Unlabeled Data., and . ICDM, page 102-111. IEEE, (2020)Learning Maximum Lag for Grouped Graphical Granger Models.. ICDM Workshops, page 217-224. IEEE Computer Society, (2010)Learning Global Transparent Models consistent with Local Contrastive Explanations., , , and . NeurIPS, (2020)Robust Pattern Recognition Scheme for Devanagari Script., , and . CIS (1), volume 3801 of Lecture Notes in Computer Science, page 1021-1026. Springer, (2005)Empirical or Invariant Risk Minimization? A Sample Complexity Perspective., , , , and . ICLR, OpenReview.net, (2021)Trust Regions for Explanations via Black-Box Probabilistic Certification., , , and . ICML, OpenReview.net, (2024)Generating Contrastive Explanations with Monotonic Attribute Functions., , , , , and . CoRR, (2019)