23 citations · 38 across the 8 of their papers we have counts for
8 papers
Power Constrained Nonstationary Bandits with Habituation and Recovery Dynamics
Fengxu Li, Stephanie M. Carpenter, Matthew P. Buman +1
A common challenge for decision makers is selecting actions whose rewards are unknown and evolve over time based on prior policies. For instance, repeated use may reduce an action'…
LLM-Powered Prediction of Hyperglycemia and Discovery of Behavioral Treatment Pathways from Wearables and Diet
Abdullah Mamun, Asiful Arefeen, Susan B. Racette +4
Postprandial hyperglycemia, marked by the blood glucose level exceeding the normal range after consuming a meal, is a critical indicator of progression toward type 2 diabetes in pe…
Role of Mixup in Topological Persistence Based Knowledge Distillation for Wearable Sensor Data
Eun Som Jeon, Hongjun Choi, Matthew P. Buman +1
The analysis of wearable sensor data has enabled many successes in several applications. To represent the high-sampling rate time-series with sufficient detail, the use of topologi…
Multimodal Physical Activity Forecasting in Free-Living Clinical Settings: Hunting Opportunities for Just-in-Time Interventions
Abdullah Mamun, Krista S. Leonard, Megan E. Petrov +2
Objective: This research aims to develop a lifestyle intervention system, called MoveSense, that forecasts a patient's activity behavior to allow for early and personalized interve…
Topological Persistence Guided Knowledge Distillation for Wearable Sensor Data
Eun Som Jeon, Hongjun Choi, Ankita Shukla +4
Deep learning methods have achieved a lot of success in various applications involving converting wearable sensor data to actionable health insights. A common application areas is…
Role of Data Augmentation Strategies in Knowledge Distillation for Wearable Sensor Data
Eun Som Jeon, Anirudh Som, Ankita Shukla +3
Deep neural networks are parametrized by several thousands or millions of parameters, and have shown tremendous success in many classification problems. However, the large number o…
Unsupervised Pre-trained Models from Healthy ADLs Improve Parkinson's Disease Classification of Gait Patterns
Anirudh Som, Narayanan Krishnamurthi, Matthew Buman +1
Application and use of deep learning algorithms for different healthcare applications is gaining interest at a steady pace. However, use of such algorithms can prove to be challeng…
PI-Net: A Deep Learning Approach to Extract Topological Persistence Images
Anirudh Som, Hongjun Choi, Karthikeyan Natesan Ramamurthy +2
Topological features such as persistence diagrams and their functional approximations like persistence images (PIs) have been showing substantial promise for machine learning and c…