37 citations · 83 across the 10 of their papers we have counts for
10 papers
Towards Low-Energy Adaptive Personalization for Resource-Constrained Devices
Yushan Huang, Josh Millar, Yuxuan Long +2
The personalization of machine learning (ML) models to address data drift is a significant challenge in the context of Internet of Things (IoT) applications. Presently, most approa…
Low-Energy On-Device Personalization for MCUs
Yushan Huang, Ranya Aloufi, Xavier Cadet +3
Microcontroller Units (MCUs) are ideal platforms for edge applications due to their low cost and energy consumption, and are widely used in various applications, including personal…
Effective Abnormal Activity Detection on Multivariate Time Series Healthcare Data
Mengjia Niu, Yuchen Zhao, Hamed Haddadi
Multivariate time series (MTS) data collected from multiple sensors provide the potential for accurate abnormal activity detection in smart healthcare scenarios. However, anomalies…
Information Theory Inspired Pattern Analysis for Time-series Data
Yushan Huang, Yuchen Zhao, Alexander Capstick +3
Current methods for pattern analysis in time series mainly rely on statistical features or probabilistic learning and inference methods to identify patterns and trends in the data.…
Using Entropy Measures for Monitoring the Evolution of Activity Patterns
Yushan Huang, Yuchen Zhao, Hamed Haddadi +1
In this work, we apply information theory inspired methods to quantify changes in daily activity patterns. We use in-home movement monitoring data and show how they can help indica…
Towards Battery-Free Machine Learning and Inference in Underwater Environments
Yuchen Zhao, Sayed Saad Afzal, Waleed Akbar +5
This paper is motivated by a simple question: Can we design and build battery-free devices capable of machine learning and inference in underwater environments? An affirmative answ…
Designing A Clinically Applicable Deep Recurrent Model to Identify Neuropsychiatric Symptoms in People Living with Dementia Using In-Home Monitoring Data
Francesca Palermo, Honglin Li, Alexander Capstick +6
Agitation is one of the neuropsychiatric symptoms with high prevalence in dementia which can negatively impact the Activities of Daily Living (ADL) and the independence of individu…
Multimodal Federated Learning on IoT Data
Yuchen Zhao, Payam Barnaghi, Hamed Haddadi
Federated learning is proposed as an alternative to centralized machine learning since its client-server structure provides better privacy protection and scalability in real-world…
Semi-supervised Federated Learning for Activity Recognition
Yuchen Zhao, Hanyang Liu, Honglin Li +2
Training deep learning models on in-home IoT sensory data is commonly used to recognise human activities. Recently, federated learning systems that use edge devices as clients to s…
Using Metrics Suites to Improve the Measurement of Privacy in Graphs
Isabel Wagner, Yuchen Zhao
Social graphs are widely used in research (e.g., epidemiology) and business (e.g., recommender systems). However, sharing these graphs poses privacy risks because they contain sens…