Walter H. Dempsey

According to our database1, Walter H. Dempsey authored at least 13 papers between 2017 and 2025.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

On csauthors.net:

Bibliography

2025
Practical considerations when designing an online learning algorithm for an app-based mHealth intervention.
CoRR, November, 2025

2024
Non-Stationary Latent Auto-Regressive Bandits.
CoRR, 2024

RoME: A Robust Mixed-Effects Bandit Algorithm for Optimizing Mobile Health Interventions.
Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

2023
Effectiveness of gamified team competition as mHealth intervention for medical interns: a cluster micro-randomized trial.
npj Digit. Medicine, 2023

A randomized trial of a mobile health intervention to augment cardiac rehabilitation.
npj Digit. Medicine, 2023

Debiased Machine Learning and Network Cohesion for Doubly-Robust Differential Reward Models in Contextual Bandits.
CoRR, 2023

CataBEEM: Integrating Latent Interaction Categories in Node-wise Community Detection Models for Network Data.
Proceedings of the International Conference on Machine Learning, 2023

2022
Kernel Multimodal Continuous Attention.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021
Kernel Deformed Exponential Families for Sparse Continuous Attention.
CoRR, 2021

2020
A Functional EM Algorithm for Panel Count Data with Missing Counts.
CoRR, 2020

A Robust Functional EM Algorithm for Incomplete Panel Count Data.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2018
Just-in-Time but Not Too Much: Determining Treatment Timing in Mobile Health.
Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 2018

2017
iSurvive: An Interpretable, Event-time Prediction Model for mHealth.
Proceedings of the 34th International Conference on Machine Learning, 2017


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