Publications

(2020). Trajectory Inspection: A Method for Iterative Clinician-Driven Design of Reinforcement Learning Studies. arXiv preprint arXiv:2010.04279.

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(2020). Treatment Policy Learning in Multiobjective Settings with Fully Observed Outcomes. Proceedings of the 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD).

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(2020). Robustly Extracting Medical Knowledge from EHRs: A Case Study of Learning a Health Knowledge Graph. Proceedings of the Pacific Symposium on Biocomputing (PSB).

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(2020). Robust Benchmarking for Machine Learning of Clinical Entity Extraction. Proceedings of the Machine Learning for Healthcare Conference.

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(2020). Predicting Remission Among Patients With Rheumatoid Arthritis Starting Tocilizumab Monotherapy: Model Derivation and Remission Score Development. ACR Open Rheumatology.

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(2020). Predicting human health from biofluid-based metabolomics using machine learning. Scientific Reports.

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(2020). Generalization Bounds and Representation Learning for Estimation of Potential Outcomes and Causal Effects.

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(2020). Fast, Structured Clinical Documentation via Contextual Autocomplete. Proceedings of the Machine Learning for Healthcare Conference.

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(2020). Estimation of Bounds on Potential Outcomes For Decision Making. Proceedings of the Thirty-Seventh International Conference on Machine Learning (ICML).

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(2020). Empirical Study of the Benefits of Overparameterization in Learning Latent Variable Models. Proceedings of the Thirty-Seventh International Conference on Machine Learning (ICML).

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(2020). Consistent Estimators for Learning to Defer to an Expert. Proceedings of the Thirty-Seventh International Conference on Machine Learning (ICML).

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(2020). Characterization of Overlap in Observational Studies. Proceedings of the Twenty-Third International Conference on Artificial Intelligence and Statistics (AISTATS).

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(2020). A decision algorithm to promote outpatient antimicrobial stewardship for uncomplicated urinary tract infection. Science Translational Medicine.

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(2019). Derivation and validation of a machine learning record linkage algorithm between emergency medical services and the emergency department. Journal of the American Medical Informatics Association.

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(2019). Train and Test Tightness of LP Relaxations in Structured Prediction. Journal of Machine Learning Research.

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(2019). Support and Invertibility in Domain-Invariant Representations. Proceedings of the Twenty-Second International Conference on Artificial Intelligence and Statistics (AISTATS).

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(2019). Overcomplete Independent Component Analysis via SDP. Proceedings of the Twenty-Second International Conference on Artificial Intelligence and Statistics (AISTATS).

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(2019). Guidelines for reinforcement learning in healthcare.. Nature medicine.

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(2019). Counterfactual Off-Policy Evaluation with Gumbel-Max Structural Causal Models. Proceedings of the Thirty-Sixth International Conference on Machine Learning (ICML).

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(2019). Block Stability for MAP Inference. Proceedings of the Twenty-Second International Conference on Artificial Intelligence and Statistics (AISTATS).

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(2018). Why Is My Classifier Discriminatory?. Proceedings of the 32nd International Conference on Neural Information Processing Systems.

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(2018). Semi-Amortized Variational Autoencoders. Proceedings of the 35th International Conference on Machine Learning (ICML).

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(2018). Recurrent Neural Networks for Multivariate Time Series with Missing Values. Nature Scientific Reports.

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(2018). Optimality of Approximate Inference Algorithms on Stable Instances. Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics (AI-STATS).

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(2018). Max-margin learning with the Bayes Factor. Proceedings of the Conference on Uncertainty in Artificial Intelligence (UAI).

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(2018). Machine Learning Analysis of Heterogeneity in the Effect of Student Mindset Interventions. arXiv preprint arXiv:1811.05975.

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(2018). Learning Weighted Representations for Generalization Across Designs. ArXiv e-prints arXiv:1802.08598.

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(2018). Learning Topic Models - Provably and Efficiently. Communications of the ACM.

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(2018). Evaluating Reinforcement Learning Algorithms in Observational Health Settings.

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(2018). Cell-specific prediction and application of drug-induced gene expression profiles. Proceedings of the Pacific Symposium on Biocomputing (PSB).

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(2017). Using Machine Learning to Recommend Oncology Clinical Trials. Machine Learning for Health Care (Clinical abstract).

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(2017). Structured Inference Networks for Nonlinear State Space Models. Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence.

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(2017). Simultaneous Learning of Trees and Representations for Extreme Classification and Density Estimation. Proceedings of the 34th International Conference on Machine Learning.

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(2017). Objective Assessment of Depressive Symptoms with Machine Learning and Wearable Sensors Data. Proceedings of the Seventh International Conference on Affective Computing and Intelligent Interaction (ACII).

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(2017). Learning a Health Knowledge Graph from Electronic Medical Records. Nature Scientific Reports.

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(2017). Grounded Recurrent Neural Networks. ArXiv e-prints arXiv:1705.08557.

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(2017). Estimating individual treatment effect: generalization bounds and algorithms. Proceedings of the 34th International Conference on Machine Learning.

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(2017). Electronic phenotyping with APHRODITE and the Observational Health Sciences and Informatics (OHDSI) data network. Proceedings of the AMIA Summit on Clinical Research Informatics (CRI).

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(2017). Early Identification of Patients with Acute Decompensated Heart Failure. Journal of Cardiac Failure.

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(2017). Discourse-Based Objectives for Fast Unsupervised Sentence Representation Learning. arXiv preprint arXiv:1705.00557.

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(2017). Creating an Automated Trigger for Sepsis Clinical Decision Support at Emergency Department Triage using Machine Learning. PLoS ONE.

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(2017). Contextual Autocomplete: A Novel User Interface Using Machine Learning to Improve Ontology Usage and Structured Data Capture for Presenting Problems in the Emergency Department. bioRxiv.

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(2017). Causal Effect Inference with Deep Latent-Variable Models. Proceedings of the 31st International Conference on Neural Information Processing Systems.

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(2016). Train and Test Tightness of LP Relaxations in Structured Prediction. Proceedings of The 33rd International Conference on Machine Learning.

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(2016). Tightness of LP Relaxations for Almost Balanced Models. Proceedings of the 19th International Conference on Artificial Intelligence and Statistics.

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(2016). Population-Level Prediction of Type 2 Diabetes using Claims Data and Analysis of Risk Factors. Big Data.

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(2016). Multi-task Prediction of Disease Onsets from Longitudinal Laboratory Tests. Proceedings of the 1st Machine Learning for Healthcare Conference.

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(2016). Learning Representations for Counterfactual Inference. Proceedings of The 33rd International Conference on Machine Learning.

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(2016). Learning Low-Dimensional Representations of Medical Concepts. Proceedings of the AMIA Summit on Clinical Research Informatics (CRI).

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(2016). Identifiable Phenotyping using Constrained Non-Negative Matrix Factorization. Proceedings of the 1st Machine Learning for Healthcare Conference.

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(2016). Electronic Medical Record Phenotyping using the Anchor & Learn Framework. Journal of the American Medical Informatics Association (JAMIA).

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(2016). Comparison of approaches for heart failure case identification from electronic health record data. JAMA Cardiology.

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(2016). Clinical Tagging with Joint Probabilistic Models. Proceedings of the 1st Machine Learning for Healthcare Conference.

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(2016). Character-Aware Neural Language Models. Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence.

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(2015). Visual Exploration of Temporal Data in Electronic Medical Records. Proceedings of the American Medical Informatics Association (AMIA) Annual Symposium (Abstract).

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(2015). Temporal Convolutional Neural Networks for Diagnosis from Lab Tests. arXiv:1511.07938.

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(2015). Predicting chronic comorbid conditions of type 2 diabetes in Newly-Diagnosed Diabetic Patients. Value in Health (Abstract).

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(2015). How Hard is Inference for Structured Prediction?. Proceedings of the 32nd International Conference on Machine Learning (ICML).

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(2015). Deep Kalman Filters. arXiv:1511.05121.

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(2015). Barrier Frank-Wolfe for Marginal Inference. Proceedings of the 28th International Conference on Neural Information Processing Systems.

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(2015). Anchored Discrete Factor Analysis. arXiv:1511.03299.

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(2015). A Fast Variational Approach for Learning Markov Random Field Language Models. Proceedings of the 32nd International Conference on Machine Learning (ICML).

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(2014). Using Anchors to Estimate Clinical State without Labeled Data. Proceedings of the American Medical Informatics Association (AMIA) Annual Symposium.

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(2014). Unsupervised Learning of Disease Progression Models. Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining.

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(2014). Understanding the Bethe Approximation: When and How can it go Wrong?. Proceedings of the Thirtieth Conference on Uncertainty in Artificial Intelligence (UAI-14).

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(2014). Lifted Tree-Reweighted Variational Inference. Proceedings of the Thirtieth Conference on Uncertainty in Artificial Intelligence (UAI-14).

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(2014). Instance Segmentation of Indoor Scenes using a Coverage Loss. Proceedings of the 13th European Conference on Computer Vision (ECCV).

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(2013). Unsupervised Learning of Noisy-Or Bayesian Networks. Proceedings of the Twenty-Ninth Conference on Uncertainty in Artificial Intelligence (UAI-13).

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(2013). SparsityBoost: A New Scoring Function for Learning Bayesian Network Structure. Proceedings of the Twenty-Ninth Conference on Uncertainty in Artificial Intelligence (UAI-13).

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(2013). Predicting Chief Complaints at Triage Time in the Emergency Department. NeurIPS Workshop on Machine Learning for Clinical Data Analysis and Healthcare.

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(2013). Discovering Hidden Variables in Noisy-Or Networks using Quartet Tests. Advances in Neural Information Processing Systems 26.

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(2013). A Practical Algorithm for Topic Modeling with Provable Guarantees. Proceedings of the International Conference on Machine Learning (ICML).

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(2012). Probabilistic models for personalizing web search. Proceedings of the Fifth ACM International Conference on Web Search and Data Mining.

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(2012). Introduction to Dual Decomposition for Inference. Optimization for Machine Learning.

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(2012). Efficiently Searching for Frustrated Cycles in MAP Inference. Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence (UAI-12).

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(2012). A Comparison of Dimensionality Reduction Techniques for Unstructured Clinical Text. ICML 2012 Workshop on Clinical Data Analysis.

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(2011). Personalizing web search results by reading level. Proceedings of the 20th ACM International Conference on Information and Knowledge Management.

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(2011). Complexity of Inference in Latent Dirichlet Allocation. Advances in Neural Information Processing Systems 24.

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(2010). On Dual Decomposition and Linear Programming Relaxations for Natural Language Processing. Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing (EMNLP).

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(2010). More data means less inference: A pseudo-max approach to structured learning. Advances in Neural Information Processing Systems 23.

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(2010). Learning Efficiently with Approximate Inference via Dual Losses. Proceedings of the 27th International Conference on Machine Learning (ICML).

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(2010). Learning Bayesian Network Structure using LP Relaxations. Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AI-STATS).

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(2010). Dual Decomposition for Parsing with Non-Projective Head Automata. Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing (EMNLP).

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(2009). Tree Block Coordinate Descent for MAP in Graphical Models. Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics (AI-STATS).

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(2009). Scaling All-Pairs Overlay Routing. CoNEXT ‘09: Proceedings of the 5th international conference on Emerging networking experiments and technologies.

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(2009). Clusters and Coarse Partitions in LP Relaxations. Advances in Neural Information Processing Systems 21.

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(2008). Tightening LP Relaxations for MAP using Message-Passing. 24th Conference on Uncertainty in Artificial Intelligence.

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(2008). New Outer Bounds on the Marginal Polytope. Advances in Neural Information Processing Systems 20.

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(2007). Probabilistic Modeling of Systematic Errors in Two-Hybrid Experiments. Pacific Symposium on Biocomputing.

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(2005). BLOG: probabilistic models with unknown objects. IJCAI'05: Proceedings of the 19th international joint conference on Artificial intelligence.

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(2005). Approximate Inference for Infinite Contingent Bayesian Networks. Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics.

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