Peter Schulam

Publication Activity (10 Years)

Years Active: 2013-2023
Publications (10 Years): 16

Top Topics

Observational Data

Gaussian Process

Complex Diseases

Machine Learning

Top Venues

J. Mach. Learn. Res.

Publications

Weston Feely, Prabhakar Gupta, Manas Ranjan Mohanty, Timothy Chon, Tuhin Kundu, Vijit Singh, Sandeep Atluri, Tanya Roosta, Viviane Ghaderi, Peter Schulam
QCon at SemEval-2023 Task 10: Data Augmentation and Model Ensembling for Detection of Online Sexism. SemEval@ACL (2023)
Peter Schulam, Ion Muslea
Improving the Exploration/Exploitation Trade-Off in Web Content Discovery. WWW (Companion Volume) (2023)
Iiris Sundin, Peter Schulam, Eero Siivola, Aki Vehtari, Suchi Saria, Samuel Kaski
Active Learning for Decision-Making from Imbalanced Observational Data. ICML (2019)
Peter Schulam, Suchi Saria
Can You Trust This Prediction? Auditing Pointwise Reliability After Learning. AISTATS (2019)
Peter Schulam, Suchi Saria
Auditing Pointwise Reliability Subsequent to Training. CoRR (2019)
Iiris Sundin, Peter Schulam, Eero Siivola, Aki Vehtari, Suchi Saria, Samuel Kaski
Active Learning for Decision-Making from Imbalanced Observational Data. CoRR (2019)
Adarsh Subbaswamy, Peter Schulam, Suchi Saria
Preventing Failures Due to Dataset Shift: Learning Predictive Models That Transport. AISTATS (2019)
Peter Schulam, Suchi Saria
Discretizing Logged Interaction Data Biases Learning for Decision-Making. CoRR (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
Machine Learning for Health (ML4H) Workshop at NeurIPS 2018. CoRR (2018)
Adarsh Subbaswamy, Peter Schulam, Suchi Saria
Learning Predictive Models That Transport. CoRR (2018)
Marzyeh Ghassemi, Tristan Naumann, Peter Schulam, Andrew L. Beam, Rajesh Ranganath
Opportunities in Machine Learning for Healthcare. CoRR (2018)
Peter Schulam, Suchi Saria
What-If Reasoning with Counterfactual Gaussian Processes. CoRR (2017)
Peter Schulam, Suchi Saria
Reliable Decision Support using Counterfactual Models. NIPS (2017)
Peter Schulam, Suchi Saria
Integrative Analysis using Coupled Latent Variable Models for Individualizing Prognoses. J. Mach. Learn. Res. 17 (2016)
Peter Schulam, Raman Arora
Disease Trajectory Maps. CoRR (2016)
Peter Schulam, Raman Arora
Disease Trajectory Maps. NIPS (2016)
Peter Schulam, Fredrick Wigley, Suchi Saria
Clustering Longitudinal Clinical Marker Trajectories from Electronic Health Data: Applications to Phenotyping and Endotype Discovery. AAAI (2015)
Peter Schulam, Suchi Saria
A Framework for Individualizing Predictions of Disease Trajectories by Exploiting Multi-Resolution Structure. NIPS (2015)
Peter Schulam, Colin Ligon, Robert Wise, Laura K. Hummers, Fredrick Wigley, Suchi Saria
A Probabilistic Graphical Model for Individualizing Prognosis in Chronic, Complex Diseases. AMIA (2015)
Peter Schulam, Roni Rosenfeld, Premkumar T. Devanbu
Building Statistical Language Models of code. DAPSE@ICSE (2013)