Peter Schulam

Orcid: 0009-0007-3515-026X

Affiliations:
  • Amazon Alexa, USA
  • Johns Hopkins University, Baltimore, MD, USA (PhD)
  • Carnegie Mellon University, Pittsburgh, PA, USA (former)


According to our database1, Peter Schulam authored at least 28 papers between 2010 and 2026.

Collaborative distances:

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

Online presence:

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Bibliography

2026
Evaluating the Utility of Grounding Documents with Reference-Free LLM-based Metrics.
CoRR, January, 2026

2023
Improving the Exploration/Exploitation Trade-Off in Web Content Discovery.
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.
Proceedings of the The 17th International Workshop on Semantic Evaluation, 2023

2019
Auditing Pointwise Reliability Subsequent to Training.
CoRR, 2019

Active Learning for Decision-Making from Imbalanced Observational Data.
Proceedings of the 36th International Conference on Machine Learning, 2019

Preventing Failures Due to Dataset Shift: Learning Predictive Models That Transport.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

Can You Trust This Prediction? Auditing Pointwise Reliability After Learning.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018
Learning Predictive Models That Transport.
CoRR, 2018

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

Discretizing Logged Interaction Data Biases Learning for Decision-Making.
CoRR, 2018

Opportunities in Machine Learning for Healthcare.
CoRR, 2018

2017
What-If Reasoning with Counterfactual Gaussian Processes.
CoRR, 2017

Reliable Decision Support using Counterfactual Models.
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.
J. Mach. Learn. Res., 2016

Disease Trajectory Maps.
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.
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.
Proceedings of the AMIA 2015, 2015

Clustering Longitudinal Clinical Marker Trajectories from Electronic Health Data: Applications to Phenotyping and Endotype Discovery.
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2014
Diagnostic techniques for spoken keyword discovery.
Proceedings of the 15th Annual Conference of the International Speech Communication Association, 2014

2013
Erratum to: Large, huge or gigantic? Identifying and encoding intensity relations among adjectives in WordNet.
Lang. Resour. Evaluation, 2013

Large, huge or gigantic? Identifying and encoding intensity relations among adjectives in WordNet.
Lang. Resour. Evaluation, 2013

Robust audio-codebooks for large-scale event detection in consumer videos.
Proceedings of the 14th Annual Conference of the International Speech Communication Association, 2013

Building Statistical Language Models of code.
Proceedings of the 1st International Workshop on Data Analysis Patterns in Software Engineering, 2013

2012

Beyond audio and video retrieval: towards multimedia summarization.
Proceedings of the International Conference on Multimedia Retrieval, 2012

Event-based Video Retrieval Using Audio.
Proceedings of the 13th Annual Conference of the International Speech Communication Association, 2012

Generating Natural Language Summaries for Multimedia.
Proceedings of the INLG 2012 - Proceedings of the Seventh International Natural Language Generation Conference, 30 May 2012, 2012

2010
Automatically Determining the Semantic Gradation of German Adjectives.
Proceedings of the Semantic Approaches in Natural Language Processing: Proceedings of the 10th Conference on Natural Language Processing, 2010


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