Peter Schulam

According to our database, Peter Schulam authored at least 18 papers between 2013 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Improving the Exploration/Exploitation Trade-Off in Web Content Discovery.

Peter Schulam, Ion Muslea

Proceedings of the Companion Proceedings of the ACM Web Conference 2023, 2023

QCon at SemEval-2023 Task 10: Data Augmentation and Model Ensembling for Detection of Online Sexism.

Weston Feely, Prabhakar Gupta, Manas Ranjan Mohanty, Timothy Chon, Tuhin Kundu, Vijit Singh, Sandeep Atluri, Tanya Roosta, Viviane Ghaderi, Peter Schulam

Proceedings of the The 17th International Workshop on Semantic Evaluation, 2023

2019

Auditing Pointwise Reliability Subsequent to Training.

Peter Schulam, Suchi Saria

CoRR, 2019

Active Learning for Decision-Making from Imbalanced Observational Data.

Iiris Sundin, Peter Schulam, Eero Siivola, Aki Vehtari, Suchi Saria, Samuel Kaski

Proceedings of the 36th International Conference on Machine Learning, 2019

Preventing Failures Due to Dataset Shift: Learning Predictive Models That Transport.

Adarsh Subbaswamy, Peter Schulam, Suchi Saria

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

Can You Trust This Prediction? Auditing Pointwise Reliability After Learning.

Peter Schulam, Suchi Saria

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

Learning Predictive Models That Transport.

Adarsh Subbaswamy, Peter Schulam, Suchi Saria

CoRR, 2018

Machine Learning for Health (ML4H) Workshop at NeurIPS 2018.

Natalia Antropova, Andrew L. Beam, Brett K. Beaulieu-Jones, Irene Chen, Corey Chivers, Adrian V. Dalca, Samuel G. Finlayson, Madalina Fiterau, Jason Alan Fries, Marzyeh Ghassemi, Mike Hughes, Bruno Jedynak, Jasvinder S. Kandola, Matthew B. A. McDermott, Tristan Naumann, Peter Schulam, Farah Shamout, Alexandre Yahi

CoRR, 2018

Discretizing Logged Interaction Data Biases Learning for Decision-Making.

Peter Schulam, Suchi Saria

CoRR, 2018

Opportunities in Machine Learning for Healthcare.

Marzyeh Ghassemi, Tristan Naumann, Peter Schulam, Andrew L. Beam, Rajesh Ranganath

CoRR, 2018

2017

What-If Reasoning with Counterfactual Gaussian Processes.

Peter Schulam, Suchi Saria

CoRR, 2017

Reliable Decision Support using Counterfactual Models.

Peter Schulam, Suchi Saria

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

2016

Integrative Analysis using Coupled Latent Variable Models for Individualizing Prognoses.

Peter Schulam, Suchi Saria

J. Mach. Learn. Res., 2016

Disease Trajectory Maps.

Peter Schulam, Raman Arora

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

2015

A Framework for Individualizing Predictions of Disease Trajectories by Exploiting Multi-Resolution Structure.

Peter Schulam, Suchi Saria

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

A Probabilistic Graphical Model for Individualizing Prognosis in Chronic, Complex Diseases.

Peter Schulam, Colin Ligon, Robert Wise, Laura K. Hummers, Fredrick Wigley, Suchi Saria

Proceedings of the AMIA 2015, 2015

Clustering Longitudinal Clinical Marker Trajectories from Electronic Health Data: Applications to Phenotyping and Endotype Discovery.

Peter Schulam, Fredrick Wigley, Suchi Saria

Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2013

Building Statistical Language Models of code.

Peter Schulam, Roni Rosenfeld, Premkumar T. Devanbu

Proceedings of the 1st International Workshop on Data Analysis Patterns in Software Engineering, 2013