Lage I, Chen E, He J, Narayanan M, Gershman S, Kim B, Doshi-Velez F.
An Evaluation of the Human-Interpretability of Explanation. Conference on Neural Information Processing Systems (NeurIPS) Workshop on Correcting and Critiquing Trends in Machine Learning. 2018.
Paper Pradier MF, Pan W, Yao J, Ghosh S, Doshi-Velez F.
Projected BNNs: Avoiding weight-space pathologies by projecting neural network weights. Conference on Neural Information Processing Systems (NeurIPS) Workshop on Bayesian Deep Learning . 2018.
Paper Fernandez-Pradier M, Pan W, Yao M, Singh R, Doshi-Velez F.
Hierarchical Stick-breaking Feature Paintbox. Conference on Neural Information Processing Systems (NeurIPS) Workshop on All of Bayesian Nonparametrics. 2018.
Paper Futoma J, Hughes MC, Doshi-Velez F.
Prediction-Constrained POMDPs. Conference on Neural Information Processing Systems (NeurIPS) Workshop on Reinforcement Learning under Partial Observability . 2018.
Paper Parbhoo S, Gottesman O, Ross AS, Komorowski M, Faisal A, Bon I, Roth V, Doshi-Velez F.
Improving counterfactual reasoning with kernelised dynamic mixing models. PLoS ONE . 2018;13 (11).
Paper Lage I, Ross A, Kim B, Gershman S, Doshi-Velez F.
Human-in-the-Loop Interpretability Prior. Conference on Neural Information Processing Systems (NeurIPS). 2018.
Paper Wu M, Hughes M, Parbhoo S, Zazzi M, Roth V, Doshi-Velez F.
Beyond Sparsity: Tree Regularization of Deep Models for Interpretability. Association for the Advancement of Artificial Intelligence (AAAI). 2018.
Paper Masood MA, Doshi-Velez F.
Diversity-Inducing Policy Gradient: Using MMD to find a set of policies that are diverse in terms of stete-visitation. International Conference on Machine Learning (ICML) Exploration in Reinforcement Learning Workshop. 2018.
Paper Peng X, Ding Y, Wihl D, Gottesman O, Komorowski M, Lehman L-wei H, Ross A, Faisal A, Doshi-Velez F.
Improving Sepsis Treatment Strategies by Combining Deep and Kernel-Based Reinforcement Learning. American Medical Informatics Association (AMIA) Annual Symposium. 2018.
Paper Ghosh S, Yao J, Doshi-Velez F.
Structured Variational Learning of Bayesian Neural Networks with Horseshoe Priors, in
Proceedings of the 35th International Conference on Machine Learning (ICML). Vol 80. Stockholm, Sweden ; 2018.
Paper Depeweg S, Hernandez-Lobato JM, Doshi-Velez F, Udluft S.
Decomposition of Uncertainty in Bayesian Deep Learning for Efficient and Risk-sensitive Learning, in
Proceedings of the 35th International Conference on Machine Learning (ICML). Vol 80. Stockholm, Sweden ; 2018.
Paper Gottesman O, Pan W, Doshi-Velez F.
Weighted Tensor Decomposition for Learning Latent Variables with Partial Data, in
Proceedings of the 21st International Conference on Artificial Intelligence and Statistics (AISTATS) 2018. Vol 84. Lanzarote, Spain ; 2018.
Paper Hughes MC, Hope G, Weiner L, Thomas H. McCoy J, Perlis RH, Sudderth E, Doshi-Velez F.
Semi-Supervised Prediction-Constrained Topic Models, in
Proceedings of the 21st International Conference on Artificial Intelligence and Statistics (AISTATS) 2018. Vol 84. Lanzarote, Spain ; 2018.
Paper Amir O, Doshi-Velez F, Sarne D.
Agent Strategy Summarization. Autonomous Agents and Multiagent Systems, Blue Sky Ideas Track. 2018.
Paper Doshi-Velez F, Kortz M, Budish R, Bavitz C, Gershman S, O'Brien D, Shieber S, Waldo J, Weinberger D, Wood A.
Accountability of AI Under the Law: The Role of Explanation. Privacy Law Scholars Conference. 2018.
Paper Jin L, Doshi-Velez F, Miller T, Schuler W, Schwartz L.
Unsupervised Grammar Induction with Depth-bounded PCFG. Association for Computational Linguistics. 2018.
Paper Yao J, Killian T, Konidaris G, Doshi-Velez F.
Direct Policy Transfer via Hidden Parameter Markov Decision Processes. International Conference on Machine Learning (ICML) Workshop on Lifelong Learning,. 2018.
Paper Raghu A, Gottesman O, Liu Y, Komorowski M, Faisal A, Doshi-Velez F, Brunskill E.
Behaviour Policy Estimation in Off-Policy Policy Evaluation: Calibration Matters. International Conference on Machine Learning (ICML) Workshop on CausalML. 2018.
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