Michael C. Hughes
Orcid: 0000-0003-4859-7400Affiliations:
- Tufts University, Department of Computer Science, Medford, MA, USA
- Brown University, Department of Computer Science, Providence, RI, USA (PhD 2016)
- Olin College of Engineering, Needham, MA, USA (former)
According to our database1,
Michael C. Hughes
authored at least 54 papers
between 2010 and 2024.
Collaborative distances:
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Bibliography
2024
InterLUDE: Interactions between Labeled and Unlabeled Data to Enhance Semi-Supervised Learning.
CoRR, 2024
CoRR, 2024
Discovering group dynamics in synchronous time series via hierarchical recurrent switching-state models.
CoRR, 2024
2023
Nonparametric and Regularized Dynamical Wasserstein Barycenters for Sequential Observations.
IEEE Trans. Signal Process., 2023
Trans. Mach. Learn. Res., 2023
Accuracy versus time frontiers of semi-supervised and self-supervised learning on medical images.
CoRR, 2023
Detecting Heart Disease from Multi-View Ultrasound Images via Supervised Attention Multiple Instance Learning.
Proceedings of the Machine Learning for Healthcare Conference, 2023
A Probabilistic Method to Predict Classifier Accuracy on Larger Datasets given Small Pilot Data.
Proceedings of the Machine Learning for Health, 2023
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023
2022
Non-Parametric and Regularized Dynamical Wasserstein Barycenters for Time-Series Analysis.
CoRR, 2022
CoRR, 2022
Easy Variational Inference for Categorical Models via an Independent Binary Approximation.
Proceedings of the International Conference on Machine Learning, 2022
Proceedings of the Conference on Health, Inference, and Learning, 2022
Optimizing Early Warning Classifiers to Control False Alarms via a Minimum Precision Constraint.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022
2021
J. Artif. Intell. Res., 2021
CoRR, 2021
Proceedings of the UIST '21: The 34th Annual ACM Symposium on User Interface Software and Technology, 2021
The Tufts fNIRS Mental Workload Dataset & Benchmark for Brain-Computer Interfaces that Generalize.
Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Approximate Bayesian Computation for an Explicit-Duration Hidden Markov Model of COVID-19 Hospital Trajectories.
Proceedings of the Machine Learning for Healthcare Conference, 2021
A New Semi-supervised Learning Benchmark for Classifying View and Diagnosing Aortic Stenosis from Echocardiograms.
Proceedings of the Machine Learning for Healthcare Conference, 2021
Proceedings of the 38th International Conference on Machine Learning, 2021
2020
A Framework for Sensorimotor Cross-Perception and Cross-Behavior Knowledge Transfer for Object Categorization.
Frontiers Robotics AI, 2020
Learning Consistent Deep Generative Models from Sparse Data via Prediction Constraints.
CoRR, 2020
Hierarchical Classification of Enzyme Promiscuity Using Positive, Unlabeled, and Hard Negative Examples.
CoRR, 2020
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020
MIMIC-Extract: a data extraction, preprocessing, and representation pipeline for MIMIC-III.
Proceedings of the ACM CHIL '20: ACM Conference on Health, 2020
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020
2019
Feature Robustness in Non-stationary Health Records: Caveats to Deployable Model Performance in Common Clinical Machine Learning Tasks.
Proceedings of the Machine Learning for Healthcare Conference, 2019
Proceedings of the Joint IEEE 9th International Conference on Development and Learning and Epigenetic Robotics, 2019
Proceedings of the Symposium on Advances in Approximate Bayesian Inference, 2019
2018
Rethinking clinical prediction: Why machine learning must consider year of care and feature aggregation.
CoRR, 2018
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018
2017
CoRR, 2017
Right for the Right Reasons: Training Differentiable Models by Constraining their Explanations.
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017
Proceedings of the 34th International Conference on Machine Learning, 2017
Proceedings of the Summit on Clinical Research Informatics, 2017
2016
"Reliable and scalable variational inference for nonparametric mixtures, topics, and sequences".
PhD thesis, 2016
2015
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015
Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015
2013
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
Effective Split-Merge Monte Carlo Methods for Nonparametric Models of Sequential Data.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012
Proceedings of the 29th International Conference on Machine Learning, 2012
Proceedings of the 2012 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, 2012
2010
Comput. Sci. Educ., 2010