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Behaviour Policy Estimation in Off-Policy Policy Evaluation: Calibration Matters. International Conference on Machine Learning (ICML) Workshop on CausalML. 2018.
Paper Sussex S, Gottesman O, Liu Y, Murphy S, Brunskill E, Doshi-Velez F.
Stitched Trajectories for Off-Policy Learning. International Conference on Machine Learning (ICML) Workshop on CausalML,. 2018.
Paper Liu Y, Gottesman O, Raghu A, Komorowski M, Faisal A, Doshi-Velez F, Brunskill E.
Representation Balancing MDPs for Off-Policy Policy Evaluation. International Conference on Machine Learning (ICML) Workshop on CausalML. 2018.
Paper Gottesman O, Doshi-Velez F.
Regularizing Tensor Decomposition Methods by Optimizing Pseudo-Data. International Conference on Machine Learning (ICML) Exploration in Reinforcement Learning Workshop,. 2018.
Paper Ross AS, Pan W, Doshi-Velez F.
Learning Qualitatively Diverse and Interpretable Rules for Classification. International Conference on Machine Learning (ICML) Workshop on Human Interpretability in Machine Learning,. 2018.
Paper Jin L, Doshi-Velez F, Miller T, Schuler W, Schwartz L.
Depth-bounding is effective: Improvements and Evaluation of Unsupervised PCFG Induction. Conference on Empirical Methods in Natural Language Processing (EMNLP) . 2018.
Paper Doshi-Velez F, Kim B.
Considerations for Evaluation and Generalization in Interpretable Machine Learning. In:
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Chapter Glueck M, Naeini MP, Doshi-Velez F, Chevalier F, Khan A, Wigdor D, Brudno M.
PhenoLines: Phenotype Comparison Visualizations for Disease Subtyping via Topic Models. IEEE Transactions on Visualization and Computer Graphics. 2018;24 (1) :371-381.
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