Publications

2018
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: Escalante H, Escalera S, Guyon I, Baró X, Güçlütürk Y, Güçlü U, van Gerven MAJ Explainable and Interpretable Models in Computer Vision and Machine Learning. 1st ed. Springer International Publishing ; 2018. 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. Paper
2017
Ghassemi M, Wu M, Hughes MC, Szolovits P, Doshi-Velez F. Predicting intervention onset in the ICU with switching state space models. American Medical Informatics Association (AMIA),. 2017. Paper
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. Conference on Visual Analytics Science and Technology (VAST),. 2017. Paper
Ross AS, Lage I, Doshi-Velez F. The Neural LASSO: Local Linear Sparsity for Interpretable Explanations. Neural Information Processing Systems (NIPS) Workshop on Transparent and Interpretable Machine Learning in Safety Critical Environments. 2017. Paper
Wu M, Hughes M, Parbhoo S, Zazzi M, Roth V, Doshi-Velez F. Beyond Sparsity: Tree Regularization of Deep Models for Interpretability. Neural Information Processing Systems (NIPS) Workshop on Transparent and Interpretable Machine Learning in Safety Critical Environments. 2017. Paper
Parbhoo S, Roth V, Doshi-Velez F. Counterfactual Reasoning with Dynamic Switching Models for HIV Therapy Selection. Neural Information Processing Systems (NIPS) Workshop on Machine Learning for Healthcare. 2017. Paper
Hughes MC, Hope G, Weiner L, McCoy TH, Perlis RH, Sudderth EB, Doshi-Velez F. Prediction-Constrained Topic Models for Antidepressant Recommendation. Neural Information Processing Systems (NIPS) Workshop on Machine Learning for Healthcare. 2017. Paper
Ghosh S, Doshi-Velez F. Model Selection in Bayesian Neural Networks via Horseshoe Priors. Neural Information Processing Systems (NIPS) Workshop on Bayesian Deep Learning. 2017. Paper
Singh R, Ling J, Doshi-Velez F. Structured Variational Autoencoders for the Beta-Bernoulli Process. Neural Information Processing Systems (NIPS) Workshop on Advances in Approximate Bayesian Inference. 2017. Paper
Tan S, Doshi-Velez F, Quiroz J, Glassman E. Clustering LaTeX Solutions to Machine Learning Assignments for Rapid Assessment. Advancing Education with Data Knowledge Discovery and Data Mining (KDD) Workshop. 2017. Paper
Depeweg S, Hernandez-Lobato JM, Doshi-Velez F, Udluft S. Uncertainty Decomposition in Bayesian Neural Networks with Latent Variables. International Conference on Machine Learning (ICML) Workshop. 2017. Paper
Parbhoo S, Bogojeska J, Zazzi M, Roth V, Doshi-Velez F. Combining Kernel and Model Based Learning for HIV Therapy Selection, in AMIA Summits on Translational Science Proceedings . Vol 2017. ; 2017 :239. Paper
Fan A, Doshi-Velez F, Miratrix L. Prior Matters: Simple and General Methods for Evaluating and Improving Topic Quality in Topic Modeling. Text as Data. 2017. Paper
Killian T, Daulton S, Konidaris G, Doshi-Velez F. Robust and Efficient Transfer Learning with Hidden Parameter Markov Decision Processes. Neural Information Processing Systems (NIPS). 2017. Paper

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