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Michael C. Hughes
- > Home > Persons > Michael C. Hughes
Publications
- 2024
- [i32]Michael T. Wojnowicz, Preetish Rath, Eric L. Miller, Jeffrey Miller, Clifford Hancock, Meghan O'Donovan, Seth Elkin-Frankston, Thaddeus Brunye, Michael C. Hughes:
Discovering group dynamics in synchronous time series via hierarchical recurrent switching-state models. CoRR abs/2401.14973 (2024) - [i31]Zhe Huang, Xiaowei Yu, Benjamin S. Wessler, Michael C. Hughes:
Semi-Supervised Multimodal Multi-Instance Learning for Aortic Stenosis Diagnosis. CoRR abs/2403.06024 (2024) - [i30]Zhe Huang, Xiaowei Yu, Dajiang Zhu, Michael C. Hughes:
InterLUDE: Interactions between Labeled and Unlabeled Data to Enhance Semi-Supervised Learning. CoRR abs/2403.10658 (2024) - 2023
- [j6]Patrick Feeney, Sarah Schneider, Panagiotis Lymperopoulos, Liping Liu, Matthias Scheutz, Michael C. Hughes:
NovelCraft: A Dataset for Novelty Detection and Discovery in Open Worlds. Trans. Mach. Learn. Res. 2023 (2023) - [j5]Kevin C. Cheng, Eric L. Miller, Michael C. Hughes, Shuchin Aeron:
Nonparametric and Regularized Dynamical Wasserstein Barycenters for Sequential Observations. IEEE Trans. Signal Process. 71: 3164-3178 (2023) - [c30]Zhe Huang, Mary-Joy Sidhom, Benjamin Wessler, Michael C. Hughes:
Fix-A-Step: Semi-supervised Learning From Uncurated Unlabeled Data. AISTATS 2023: 8373-8394 - [c29]Ethan Harvey, Wansu Chen, David M. Kent, Michael C. Hughes:
A Probabilistic Method to Predict Classifier Accuracy on Larger Datasets given Small Pilot Data. ML4H@NeurIPS 2023: 129-144 - [c28]Zhe Huang, Benjamin S. Wessler, Michael C. Hughes:
Detecting Heart Disease from Multi-View Ultrasound Images via Supervised Attention Multiple Instance Learning. MLHC 2023: 285-307 - [i29]Zhe Huang, Benjamin S. Wessler, Michael C. Hughes:
Detecting Heart Disease from Multi-View Ultrasound Images via Supervised Attention Multiple Instance Learning. CoRR abs/2306.00003 (2023) - [i28]Zhe Huang, Ruijie Jiang, Shuchin Aeron, Michael C. Hughes:
Accuracy versus time frontiers of semi-supervised and self-supervised learning on medical images. CoRR abs/2307.08919 (2023) - [i27]Patrick Feeney, Michael C. Hughes:
SINCERE: Supervised Information Noise-Contrastive Estimation REvisited. CoRR abs/2309.14277 (2023) - [i26]Ethan Harvey, Wansu Chen, David M. Kent, Michael C. Hughes:
A Probabilistic Method to Predict Classifier Accuracy on Larger Datasets given Small Pilot Data. CoRR abs/2311.18025 (2023) - 2022
- [c27]Preetish Rath, Michael C. Hughes:
Optimizing Early Warning Classifiers to Control False Alarms via a Minimum Precision Constraint. AISTATS 2022: 4895-4914 - [c25]Michael T. Wojnowicz, Shuchin Aeron, Eric L. Miller, Michael C. Hughes:
Easy Variational Inference for Categorical Models via an Independent Binary Approximation. ICML 2022: 23857-23896 - [i25]Michael T. Wojnowicz, Shuchin Aeron, Eric L. Miller, Michael C. Hughes:
Easy Variational Inference for Categorical Models via an Independent Binary Approximation. CoRR abs/2206.00093 (2022) - [i24]Patrick Feeney, Sarah Schneider, Panagiotis Lymperopoulos, Liping Liu, Matthias Scheutz, Michael C. Hughes:
NovelCraft: A Dataset for Novelty Detection and Discovery in Open Worlds. CoRR abs/2206.11736 (2022) - [i23]Zhe Huang, Mary-Joy Sidhom, Benjamin S. Wessler, Michael C. Hughes:
Fix-A-Step: Effective Semi-supervised Learning from Uncurated Unlabeled Sets. CoRR abs/2208.11870 (2022) - [i22]Kevin C. Cheng, Shuchin Aeron, Michael C. Hughes, Eric L. Miller:
Non-Parametric and Regularized Dynamical Wasserstein Barycenters for Time-Series Analysis. CoRR abs/2210.01918 (2022) - 2021
- [c24]Linfeng Liu, Michael C. Hughes, Soha Hassoun, Liping Liu:
Stochastic Iterative Graph Matching. ICML 2021: 6815-6825 - [c23]Gian Marco Visani, Alexandra Hope Lee, Cuong Nguyen, David M. Kent, John B. Wong, Joshua T. Cohen, Michael C. Hughes:
Approximate Bayesian Computation for an Explicit-Duration Hidden Markov Model of COVID-19 Hospital Trajectories. MLHC 2021: 567-613 - [c22]Zhe Huang, Gary Long, Benjamin Wessler, Michael C. Hughes:
A New Semi-supervised Learning Benchmark for Classifying View and Diagnosing Aortic Stenosis from Echocardiograms. MLHC 2021: 614-647 - [c21]Kevin C. Cheng, Shuchin Aeron, Michael C. Hughes, Eric L. Miller:
Dynamical Wasserstein Barycenters for Time-series Modeling. NeurIPS 2021: 27991-28003 - [c20]Zhe Huang, Liang Wang, Giles Blaney, Christopher Slaughter, Devon McKeon, Ziyu Zhou, Robert J. K. Jacob, Michael C. Hughes:
The Tufts fNIRS Mental Workload Dataset & Benchmark for Brain-Computer Interfaces that Generalize. NeurIPS Datasets and Benchmarks 2021 - [c19]Liang Wang, Zhe Huang, Ziyu Zhou, Devon McKeon, Giles Blaney, Michael C. Hughes, Robert J. K. Jacob:
Taming fNIRS-based BCI Input for Better Calibration and Broader Use. UIST 2021: 179-197 - [i21]Linfeng Liu, Michael C. Hughes, Liping Liu:
Modeling Graph Node Correlations with Neighbor Mixture Models. CoRR abs/2103.15966 (2021) - [i20]Alexandra Hope Lee, Panagiotis Lymperopoulos, Joshua T. Cohen, John B. Wong, Michael C. Hughes:
Forecasting COVID-19 Counts At A Single Hospital: A Hierarchical Bayesian Approach. CoRR abs/2104.09327 (2021) - [i19]Gian Marco Visani, Alexandra Hope Lee, Cuong Nguyen, David M. Kent, John B. Wong, Joshua T. Cohen, Michael C. Hughes:
Approximate Bayesian Computation for an Explicit-Duration Hidden Markov Model of COVID-19 Hospital Trajectories. CoRR abs/2105.00773 (2021) - [i18]Linfeng Liu, Michael C. Hughes, Soha Hassoun, Li-Ping Liu:
Stochastic Iterative Graph Matching. CoRR abs/2106.02206 (2021) - [i17]Patrick Feeney, Michael C. Hughes:
Evaluating the Use of Reconstruction Error for Novelty Localization. CoRR abs/2107.13379 (2021) - [i16]Zhe Huang, Gary Long, Benjamin Wessler, Michael C. Hughes:
A New Semi-supervised Learning Benchmark for Classifying View and Diagnosing Aortic Stenosis from Echocardiograms. CoRR abs/2108.00080 (2021) - [i15]Kevin C. Cheng, Shuchin Aeron, Michael C. Hughes, Eric L. Miller:
Dynamical Wasserstein Barycenters for Time-series Modeling. CoRR abs/2110.06741 (2021) - 2020
- [j3]Gyan Tatiya, Ramtin Hosseini, Michael C. Hughes, Jivko Sinapov:
A Framework for Sensorimotor Cross-Perception and Cross-Behavior Knowledge Transfer for Object Categorization. Frontiers Robotics AI 7: 522141 (2020) - [c15]Kevin C. Cheng, Shuchin Aeron, Michael C. Hughes, Erika Hussey, Eric L. Miller:
Optimal Transport Based Change Point Detection and Time Series Segment Clustering. ICASSP 2020: 6034-6038 - [i13]Gian Marco Visani, Michael C. Hughes, Soha Hassoun:
Hierarchical Classification of Enzyme Promiscuity Using Positive, Unlabeled, and Hard Negative Examples. CoRR abs/2002.07327 (2020) - 2019
- [c13]Gyan Tatiya, Ramtin Hosseini, Michael C. Hughes, Jivko Sinapov:
Sensorimotor Cross-Behavior Knowledge Transfer for Grounded Category Recognition. ICDL-EPIROB 2019: 1-6 - [i7]Kevin C. Cheng, Shuchin Aeron, Michael C. Hughes, Erika Hussey, Eric L. Miller:
Optimal Transport Based Change Point Detection and Time Series Segment Clustering. CoRR abs/1911.01325 (2019)
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last updated on 2024-04-25 02:31 CEST by the dblp team
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