Research output per year
Research output per year
- 17 results
Search results
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2024
Beyond Point Prediction: Score Matching-based Pseudolikelihood Estimation of Neural Marked Spatio-Temporal Point Process
Li, Z., Xu, Q., Xu, Z., Mei, Y., Zhao, T. & Zha, H., 2024, In: Proceedings of Machine Learning Research. 235, p. 29096-29111 16 p.Research output: Contribution to journal › Conference article › peer-review
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DeepFDR: A Deep Learning-based False Discovery Rate Control Method for Neuroimaging Data
Kim, T., Shu, H., Jia, Q. & de Leon, M. J., 2024, In: Proceedings of Machine Learning Research. 238, p. 946-954 9 p.Research output: Contribution to journal › Conference article › peer-review
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Towards the Theory of Unsupervised Federated Learning: Non-asymptotic Analysis of Federated EM Algorithms
Tian, Y., Weng, H. & Feng, Y., 2024, In: Proceedings of Machine Learning Research. 235, p. 48226-48279 54 p.Research output: Contribution to journal › Conference article › peer-review
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2023
K-Nearest-Neighbor Local Sampling Based Conditional Independence Testing
Li, S., Zhang, Y., Zhu, H., Wang, C. D., Shu, H., Chen, Z., Sun, Z. & Yang, Y., 2023, In: Advances in Neural Information Processing Systems. 36Research output: Contribution to journal › Conference article › peer-review
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MODES OF ADJUSTMENT: THERE IS MORE THAN ONE WAY TO ORGANIZE FOR RESILIENCE
Hilligoss, B., Larson, J. D., Lai, A. Y., Depuccio, M. J. & Wong, E. M., 2023, In: Academy of Management Annual Meeting Proceedings. 2023, 1Research output: Contribution to journal › Conference article › peer-review
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When do Minimax-fair Learning and Empirical Risk Minimization Coincide?
Singh, H., Kleindessner, M., Cevher, V., Chunara, R. & Russell, C., 2023, In: Proceedings of Machine Learning Research. 202, p. 31969-31989 21 p.Research output: Contribution to journal › Conference article › peer-review
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2022
At the Boundary of Law and Software: Toward Regulatory Design with Agent-Based Modeling
Benthall, S., Tschantz, M. C., Hatna, E., Epstein, J. M. & Strandburg, K. J., 2022, In: CEUR Workshop Proceedings. 3182Research output: Contribution to journal › Conference article › peer-review
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Private Sequential Hypothesis Testing for Statisticians: Privacy, Error Rates, and Sample Size
Zhang, W., Mei, Y. & Cummings, R., 2022, In: Proceedings of Machine Learning Research. 151, p. 11356-11373 18 p.Research output: Contribution to journal › Conference article › peer-review
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2021
INTERPERSONAL RELATIONSHIPS, DYNAMIC REINFORCEMENT, AND ALLIANCE PERFORMANCE: A CASE STUDY FROM HEALTH CARE
Murray, G. F., Lewis, V. A. & D'Aunno, T., 2021, In: Academy of Management Annual Meeting Proceedings.Research output: Contribution to journal › Conference article › peer-review
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Scaling up the Snap-ED toolkit interventions to improve fruit and vegetable consumption across counties in Georgia: An agent-based model
Zhang, D., Thapa, J. J., Li, G., Son, H., Chen, Z., Mu, L., Li, Y., Liu, J., Pagán, J. A. & Giabbanelli, P. J., 2021, In: Simulation Series. 53, 2, p. 571-582 12 p.Research output: Contribution to journal › Conference article › peer-review
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2020
Development of a discrete choice experiment to understand patient preferences for diabetes and hypertension management in rural Uganda
Moor, S. E., Tusubira, A. K., Akiteng, A. R., Hsieh, E., Ngaruiya, C., Rabin, T. L., Hawley, N. L., Lipska, K. J., Armstrong-Hough, M., Nalwadda, C. K., Nugent, R., Kalyesubula, R., Ssinabulya, I. & Schwartz, J. I., Apr 2020, In: The Lancet Global Health. 8, p. S22Research output: Contribution to journal › Conference article › peer-review
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Self-care practices and needs in patients with hypertension, diabetes, or both in rural Uganda: a mixed-methods study
Tusubira, A. K., Nalwadda, C. K., Akiteng, A. R., Armstrong-Hough, M., Hsieh, E., Ngaruiya, C., Rabin, T. L., Hawley, N., Lipska, K. J., Kalyesubula, R., Ssinabulya, I. & Schwartz, J. I., Apr 2020, In: The Lancet Global Health. 8, p. S19Research output: Contribution to journal › Conference article › peer-review
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2019
Automated Estimation of Food Type from Body-worn Audio and Motion Sensors in Free-Living Environments
Mirtchouk, M., McGuire, D. L., Deierlein, A. L. & Kleinberg, S., 2019, In: Proceedings of Machine Learning Research. 106, p. 641-662 22 p.Research output: Contribution to journal › Conference article › peer-review
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Using Contextual Information to Improve Blood Glucose Prediction
Akbari, M. & Chunara, R., 2019, In: Proceedings of Machine Learning Research. 106, p. 91-108 18 p.Research output: Contribution to journal › Conference article › peer-review
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2018
Differentially private change-point detection
Cummings, R., Krehbiel, S., Mei, Y., Tuo, R. & Zhang, W., 2018, In: Advances in Neural Information Processing Systems. 2018-December, p. 10825-10834 10 p.Research output: Contribution to journal › Conference article › peer-review
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2007
Individualized formative assessment in online module improves learning of glomerular filtration
Henrickson, S., Chunara, R., Cajigas, I., Gunter, H. & Bonventre, J., 2007, In: ASEE Annual Conference and Exposition, Conference Proceedings.Research output: Contribution to journal › Conference article › peer-review
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2004
Information bounds and asymptotically optimal procedures for detecting changes in decentralized decision systems
Mei, Y., 2004, In: IEEE International Symposium on Information Theory - Proceedings. p. 249 1 p.Research output: Contribution to journal › Conference article › peer-review