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Trajectory Inspection: A Method for Iterative Clinician-Driven Design of Reinforcement Learning Studies

Oct 08, 2020
Christina X. Ji, Michael Oberst, Sanjat Kanjilal, David Sontag


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PClean: Bayesian Data Cleaning at Scale with Domain-Specific Probabilistic Programming

Aug 07, 2020
Alexander K. Lew, Monica Agrawal, David Sontag, Vikash K. Mansinghka

* Added references; revised abstract 

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Robust Benchmarking for Machine Learning of Clinical Entity Extraction

Jul 31, 2020
Monica Agrawal, Chloe O'Connell, Yasmin Fatemi, Ariel Levy, David Sontag


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Fast, Structured Clinical Documentation via Contextual Autocomplete

Jul 29, 2020
Divya Gopinath, Monica Agrawal, Luke Murray, Steven Horng, David Karger, David Sontag

* Published in Machine Learning for Healthcare 2020 conference 

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Deep Contextual Clinical Prediction with Reverse Distillation

Jul 10, 2020
Rohan S. Kodialam, Rebecca Boiarsky, David Sontag


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Consistent Estimators for Learning to Defer to an Expert

Jun 02, 2020
Hussein Mozannar, David Sontag

* To appear in ICML 2020 

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Treatment Policy Learning in Multiobjective Settings with Fully Observed Outcomes

Jun 01, 2020
Sooraj Boominathan, Michael Oberst, Helen Zhou, Sanjat Kanjilal, David Sontag

* To appear at KDD'20 

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Knowledge Base Completion for Constructing Problem-Oriented Medical Records

Apr 27, 2020
James Mullenbach, Jordan Swartz, T. Greg McKelvey, Hui Dai, David Sontag


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Generalization Bounds and Representation Learning for Estimation of Potential Outcomes and Causal Effects

Jan 21, 2020
Fredrik D. Johansson, Uri Shalit, Nathan Kallus, David Sontag


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Estimation of Utility-Maximizing Bounds on Potential Outcomes

Oct 10, 2019
Maggie Makar, Fredrik D. Johansson, John Guttag, David Sontag


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Open Set Medical Diagnosis

Oct 07, 2019
Viraj Prabhu, Anitha Kannan, Geoffrey J. Tso, Namit Katariya, Manish Chablani, David Sontag, Xavier Amatriain

* Abbreviated version to appear at Machine Learning for Healthcare (ML4H) Workshop at NeurIPS 2019 

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Robustly Extracting Medical Knowledge from EHRs: A Case Study of Learning a Health Knowledge Graph

Oct 02, 2019
Irene Y. Chen, Monica Agrawal, Steven Horng, David Sontag

* 12 pages, presented at PSB 2020 

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Characterization of Overlap in Observational Studies

Jul 09, 2019
Fredrik D. Johansson, Dennis Wei, Michael Oberst, Tian Gao, Gabriel Brat, David Sontag, Kush R. Varshney


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Benefits of Overparameterization in Single-Layer Latent Variable Generative Models

Jun 28, 2019
Rares-Darius Buhai, Andrej Risteski, Yoni Halpern, David Sontag


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Counterfactual Off-Policy Evaluation with Gumbel-Max Structural Causal Models

May 17, 2019
Michael Oberst, David Sontag

* To appear in ICML 2019 

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Support and Invertibility in Domain-Invariant Representations

Mar 21, 2019
Fredrik D. Johansson, David Sontag, Rajesh Ranganath


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Overcomplete Independent Component Analysis via SDP

Jan 24, 2019
Anastasia Podosinnikova, Amelia Perry, Alexander Wein, Francis Bach, Alexandre d'Aspremont, David Sontag

* Appears in: Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics (AISTATS 2019). 21 pages 

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Prototypical Clustering Networks for Dermatological Disease Diagnosis

Nov 07, 2018
Viraj Prabhu, Anitha Kannan, Murali Ravuri, Manish Chablani, David Sontag, Xavier Amatriain


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Block Stability for MAP Inference

Oct 12, 2018
Hunter Lang, David Sontag, Aravindan Vijayaraghavan


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Semi-Amortized Variational Autoencoders

Jul 23, 2018
Yoon Kim, Sam Wiseman, Andrew C. Miller, David Sontag, Alexander M. Rush

* ICML 2018 

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Learning Representations for Counterfactual Inference

Jun 06, 2018
Fredrik D. Johansson, Uri Shalit, David Sontag

* Appeared in ICML 2016 

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Evaluating Reinforcement Learning Algorithms in Observational Health Settings

May 31, 2018
Omer Gottesman, Fredrik Johansson, Joshua Meier, Jack Dent, Donghun Lee, Srivatsan Srinivasan, Linying Zhang, Yi Ding, David Wihl, Xuefeng Peng, Jiayu Yao, Isaac Lage, Christopher Mosch, Li-wei H. Lehman, Matthieu Komorowski, Matthieu Komorowski, Aldo Faisal, Leo Anthony Celi, David Sontag, Finale Doshi-Velez


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Why Is My Classifier Discriminatory?

May 30, 2018
Irene Chen, Fredrik D. Johansson, David Sontag

* 3 figures, 8 pages, 6 page supplementary 

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Optimality of Approximate Inference Algorithms on Stable Instances

Apr 23, 2018
Hunter Lang, David Sontag, Aravindan Vijayaraghavan

* 13 pages, 2 figures 

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Learning Weighted Representations for Generalization Across Designs

Feb 26, 2018
Fredrik D. Johansson, Nathan Kallus, Uri Shalit, David Sontag


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Causal Effect Inference with Deep Latent-Variable Models

Nov 06, 2017
Christos Louizos, Uri Shalit, Joris Mooij, David Sontag, Richard Zemel, Max Welling

* Published as a conference paper at NIPS 2017 

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Grounded Recurrent Neural Networks

May 23, 2017
Ankit Vani, Yacine Jernite, David Sontag


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Estimating individual treatment effect: generalization bounds and algorithms

May 16, 2017
Uri Shalit, Fredrik D. Johansson, David Sontag

* Added name "TARNet" to refer to version with alpha = 0. Removed supp 

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Discourse-Based Objectives for Fast Unsupervised Sentence Representation Learning

Apr 23, 2017
Yacine Jernite, Samuel R. Bowman, David Sontag


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