Walter H. Dempsey — accepted AI-conference papers

2024

RoME: A Robust Mixed-Effects Bandit Algorithm for Optimizing Mobile Health Interventions

Easton Knight Huch, Jieru Shi, Madeline R Abbott, Jessica R Golbus, Alexander Moreno, Walter H. Dempsey

NeurIPS 2024poster

Mobile health leverages personalized and contextually tailored interventions optimized through bandit and reinforcement learning algorithms. In practice, however, challenges such as participant heterogeneity, nonstationarity, and nonlinear relationships hinder algorithm performance. We propose RoME,…

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2023

CataBEEM: Integrating Latent Interaction Categories in Node-wise Community Detection Models for Network Data

Yuhua Zhang, Walter H. Dempsey

ICML 2023poster

Community detection is a fundamental task in network analysis. Learning underlying network structures has brought deep insights into the understanding of complex systems. While many methods have focused on clustering nodes into blocks, few accounts for the fact that interactions may exhibit edge-lev…

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2022

Kernel Multimodal Continuous Attention

Alexander Moreno, Zhenke Wu, Supriya Nagesh, Walter H. Dempsey, James Matthew Rehg

NeurIPS 2022accept

Attention mechanisms take an expectation of a data representation with respect to probability weights. Recently, (Martins et al. 2020, 2021) proposed continuous attention mechanisms, focusing on unimodal attention densities from the exponential and deformed exponential families: the latter has spars…

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2017

iSurvive: An Interpretable, Event-time Prediction Model for mHealth

Walter H. Dempsey, Alexander Moreno, Christy K. Scott, Michael L. Dennis, David H. Gustafson, Susan A. Murphy +1

ICML 2017poster

An important mobile health (mHealth) task is the use of multimodal data, such as sensor streams and self-report, to construct interpretable time-to-event predictions of, for example, lapse to alcohol or illicit drug use. Interpretability of the prediction model is important for acceptance and adopti…

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