Public Health
Bibliographic References tagged with Public Health
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Saksono, H., Castaneda-Sceppa, C., Hoffman, J., el-Nasr, M. S. & Parker, A. G. StoryMap: Using Social Modeling and Self-Modeling to Support Physical Activity Among Families of Low-SES Backgrounds. in CHI ’21: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems 1–14 (2021 Proceedings, 2021).
Saksono, H., Castaneda-Sceppa, C., Hoffman, J., el-Nasr, M. S. & Parker, A. G. StoryMap: Using Social Modeling and Self-Modeling to Support Physical Activity Among Families of Low-SES Backgrounds. in CHI ’21: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems 1–14 (2021 Proceedings, 2021).
Xu, L. et al. Dual-Mandate Patrols: Multi-Armed Bandits for Green Security. arXiv:2009.06560 [cs, stat] (2020).
Xu, L. et al. Dual-Mandate Patrols: Multi-Armed Bandits for Green Security. arXiv:2009.06560 [cs, stat] (2020).
Prins, A., Mate, A., Killian, J., Abebe, R. & Tambe, M. Incorporating Healthcare Motivated Constraints in Restless Bandit Based Resource Allocation. NeurIPS 2020 Workshops: Challenges of Real World Reinforcement Learning, Machine Learning in Public Health (Best Lightning Paper), Machine Learning for Health (Best on Theme), Machine Learning for the Developing World (2020).
Prins, A., Mate, A., Killian, J., Abebe, R. & Tambe, M. Incorporating Healthcare Motivated Constraints in Restless Bandit Based Resource Allocation. NeurIPS 2020 Workshops: Challenges of Real World Reinforcement Learning, Machine Learning in Public Health (Best Lightning Paper), Machine Learning for Health (Best on Theme), Machine Learning for the Developing World (2020).
Mate, A., Killian, J., Xu, H., Perrault, A. & Tambe, M. Collapsing Bandits and their Application to Public Health Interventions. Advances in Neural and Information Processing Systems (NeurIPS) (2020).
Mate, A., Killian, J., Xu, H., Perrault, A. & Tambe, M. Collapsing Bandits and their Application to Public Health Interventions. Advances in Neural and Information Processing Systems (NeurIPS) (2020).
Zhang, H. et al. An empirical framework for domain generalization in clinical settings. in ACM Conference on Health, Inference, and Learning (2021).
Zhang, H. et al. An empirical framework for domain generalization in clinical settings. in ACM Conference on Health, Inference, and Learning (2021).
Wang, K., Wilder, B., Perrault, A. & Tambe, M. Automatically Learning Compact Quality-aware Surrogates for Optimization Problems. in NeurIPS (Spotlight) (2020).
Wang, K., Wilder, B., Perrault, A. & Tambe, M. Automatically Learning Compact Quality-aware Surrogates for Optimization Problems. in NeurIPS (Spotlight) (2020).
Perrault, A., Fang, F., Sinha, A. & Tambe, M. AI for Social Impact: Learning and Planning in the Data-to-Deployment Pipeline. AI Magazine (2020).
Perrault, A., Fang, F., Sinha, A. & Tambe, M. AI for Social Impact: Learning and Planning in the Data-to-Deployment Pipeline. AI Magazine (2020).
Ou, H.-C., Chen, H., Jabbari, S. & Tambe, M. Active Screening for Recurrent Diseases: A Reinforcement Learning Approach. 20th International Conference on Autonomous Agents and Multiagent Systems (AAMAS) (2021).
Ou, H.-C., Chen, H., Jabbari, S. & Tambe, M. Active Screening for Recurrent Diseases: A Reinforcement Learning Approach. 20th International Conference on Autonomous Agents and Multiagent Systems (AAMAS) (2021).
Killian, J. A., Perrault, A. & Tambe, M. Beyond “To Act or Not to Act”: Fast Lagrangian Approaches to General Multi-Action Restless Bandits. IJCAI 2021 Workshop on AI for Social Good (2021).
Killian, J. A., Perrault, A. & Tambe, M. Beyond “To Act or Not to Act”: Fast Lagrangian Approaches to General Multi-Action Restless Bandits. IJCAI 2021 Workshop on AI for Social Good (2021).
Biswas, A., Aggarwal, G., Varakantham, P. & Tambe, M. Learning Restless Bandits in Application to Call-based Preventive Care Programs for Maternal Healthcare. in IJCAI 2021 Workshop on AI for Social Good (2021).
Biswas, A., Aggarwal, G., Varakantham, P. & Tambe, M. Learning Restless Bandits in Application to Call-based Preventive Care Programs for Maternal Healthcare. in IJCAI 2021 Workshop on AI for Social Good (2021).