David A. Sontag

According to our database1, David A. Sontag authored at least 85 papers between 2005 and 2019.

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Bibliography

2019
Train and Test Tightness of LP Relaxations in Structured Prediction.
J. Mach. Learn. Res., 2019

Improving documentation of presenting problems in the emergency department using a domain-specific ontology and machine learning-driven user interfaces.
I. J. Medical Informatics, 2019

Estimation of Utility-Maximizing Bounds on Potential Outcomes.
CoRR, 2019

Open Set Medical Diagnosis.
CoRR, 2019

Robustly Extracting Medical Knowledge from EHRs: A Case Study of Learning a Health Knowledge Graph.
CoRR, 2019

Characterization of Overlap in Observational Studies.
CoRR, 2019

Benefits of Overparameterization in Single-Layer Latent Variable Generative Models.
CoRR, 2019

Counterfactual Off-Policy Evaluation with Gumbel-Max Structural Causal Models.
CoRR, 2019

Support and Invertibility in Domain-Invariant Representations.
CoRR, 2019

Overcomplete Independent Component Analysis via SDP.
CoRR, 2019

Few-Shot Learning for Dermatological Disease Diagnosis.
Proceedings of the Machine Learning for Healthcare Conference, 2019

Overcomplete Independent Component Analysis via SDP.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018
Prototypical Clustering Networks for Dermatological Disease Diagnosis.
CoRR, 2018

Block Stability for MAP Inference.
CoRR, 2018

Evaluating Reinforcement Learning Algorithms in Observational Health Settings.
CoRR, 2018

Why Is My Classifier Discriminatory?
CoRR, 2018

Semi-Amortized Variational Autoencoders.
CoRR, 2018

Learning topic models - provably and efficiently.
Commun. ACM, 2018

Max-margin learning with the Bayes factor.
Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, 2018

Cell-specific prediction and application of drug-induced gene expression .
Proceedings of the Biocomputing 2018: Proceedings of the Pacific Symposium, 2018

Optimality of Approximate Inference Algorithms on Stable Instances.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017
Alpha-expansion is Exact on Stable Instances.
CoRR, 2017

Grounded Recurrent Neural Networks.
CoRR, 2017

Causal Effect Inference with Deep Latent-Variable Models.
CoRR, 2017

Discourse-Based Objectives for Fast Unsupervised Sentence Representation Learning.
CoRR, 2017

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

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

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

2016
Electronic medical record phenotyping using the anchor and learn framework.
JAMIA, 2016

Bounding and Minimizing Counterfactual Error.
CoRR, 2016

Multi-task Prediction of Disease Onsets from Longitudinal Lab Tests.
CoRR, 2016

Structured Inference Networks for Nonlinear State Space Models.
CoRR, 2016

Identifiable Phenotyping using Constrained Non-Negative Matrix Factorization.
CoRR, 2016

Learning Representations for Counterfactual Inference.
CoRR, 2016

Simultaneous Learning of Trees and Representations for Extreme Classification, with Application to Language Modeling.
CoRR, 2016

Clinical Tagging with Joint Probabilistic Models.
CoRR, 2016

Recurrent Neural Networks for Multivariate Time Series with Missing Values.
CoRR, 2016

Multi-task Prediction of Disease Onsets from Longitudinal Laboratory Tests.
Proceedings of the 1st Machine Learning in Health Care, 2016

Train and Test Tightness of LP Relaxations in Structured Prediction.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Learning Low-Dimensional Representations of Medical Concepts.
Proceedings of the Summit on Clinical Research Informatics, 2016

Comparison of Approaches for Heart Failure Case Identification from EHR Data.
Proceedings of the AMIA 2016, 2016

Data Mining for Medical Informatics (DMMI) - Learning Health.
Proceedings of the AMIA 2016, 2016

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

2015
Temporal Convolutional Neural Networks for Diagnosis from Lab Tests.
CoRR, 2015

On the Tightness of LP Relaxations for Structured Prediction.
CoRR, 2015

Deep Kalman Filters.
CoRR, 2015

Barrier Frank-Wolfe for Marginal Inference.
CoRR, 2015

Character-Aware Neural Language Models.
CoRR, 2015

Anchored Discrete Factor Analysis.
CoRR, 2015

Incorporating Type II Error Probabilities from Independence Tests into Score-Based Learning of Bayesian Network Structure.
CoRR, 2015

Population-Level Prediction of Type 2 Diabetes From Claims Data and Analysis of Risk Factors.
Big Data, 2015

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

How Hard is Inference for Structured Prediction?
Proceedings of the 32nd International Conference on Machine Learning, 2015

Gaussian Processes for interpreting Multiple Prostate Specific Antigen measurements for Prostate Cancer Prediction.
Proceedings of the AMIA 2015, 2015

Visual Exploration of Temporal Data in Electronic Medical Records.
Proceedings of the AMIA 2015, 2015

2014
Tight Error Bounds for Structured Prediction.
CoRR, 2014

Lifted Tree-Reweighted Variational Inference.
CoRR, 2014

Understanding the Bethe Approximation: When and How can it go Wrong?
Proceedings of the Thirtieth Conference on Uncertainty in Artificial Intelligence, 2014

Unsupervised learning of disease progression models.
Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2014

Instance Segmentation of Indoor Scenes Using a Coverage Loss.
Proceedings of the Computer Vision - ECCV 2014, 2014

Using Anchors to Estimate Clinical State without Labeled Data.
Proceedings of the AMIA 2014, 2014

2013
Unsupervised Learning of Noisy-Or Bayesian Networks.
CoRR, 2013

SparsityBoost: A New Scoring Function for Learning Bayesian Network Structure.
CoRR, 2013

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

Discovering Hidden Variables in Noisy-Or Networks using Quartet Tests.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

2012
A Practical Algorithm for Topic Modeling with Provable Guarantees
CoRR, 2012

Efficiently Searching for Frustrated Cycles in MAP Inference
CoRR, 2012

Tightening LP Relaxations for MAP using Message Passing
CoRR, 2012

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

2011
Complexity of Inference in Latent Dirichlet Allocation.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

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

2010
Approximate inference in graphical models using linear programming relaxations.
PhD thesis, 2010

Learning Bayesian Network Structure using LP Relaxations.
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010

More data means less inference: A pseudo-max approach to structured learning.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Learning Efficiently with Approximate Inference via Dual Losses.
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010

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

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

2009
Tree Block Coordinate Descent for MAP in Graphical Models.
Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, 2009

Scaling all-pairs overlay routing.
Proceedings of the 2009 ACM Conference on Emerging Networking Experiments and Technology, 2009

2008
Clusters and Coarse Partitions in LP Relaxations.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008

2007
Probabilistic Modeling of Systematic Errors in Two-Hybrid Experiments.
Proceedings of the Biocomputing 2007, 2007

New Outer Bounds on the Marginal Polytope.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007

2005
BLOG: Probabilistic Models with Unknown Objects.
Proceedings of the Probabilistic, Logical and Relational Learning - Towards a Synthesis, 30. January, 2005

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


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