1 citations · 1 across the 9 of their papers we have counts for
9 papers
Dywave: Event-Aligned Dynamic Tokenization for Heterogeneous IoT Sensing Signals
Tomoyoshi Kimura, Denizhan Kara, Jinyang Li +6
Internet of Things (IoT) systems continuously collect heterogeneous sensing signals from ubiquitous sensors to support intelligent applications such as human activity analysis, emo…
Understanding the Theoretical Foundations of Deep Neural Networks through Differential Equations
Hongjue Zhao, Yizhuo Chen, Yuchen Wang +4
Deep neural networks (DNNs) have achieved remarkable empirical success, yet the absence of a principled theoretical foundation continues to hinder their systematic development. In…
PASS: Private Attributes Protection with Stochastic Data Substitution
Yizhuo Chen, Chun-Fu, Chen +3
The growing Machine Learning (ML) services require extensive collections of user data, which may inadvertently include people's private information irrelevant to the services. Vari…
SPAR: Self-supervised Placement-Aware Representation Learning for Distributed Sensing
Yizhuo Chen, Tianchen Wang, You Lyu +7
We present SPAR, a framework for self-supervised placement-aware representation learning in distributed sensing. Distributed sensing spans applications where multiple spatially dis…
SCRAG: Social Computing-Based Retrieval Augmented Generation for Community Response Forecasting in Social Media Environments
Dachun Sun, You Lyu, Jinning Li +4
This paper introduces SCRAG, a prediction framework inspired by social computing, designed to forecast community responses to real or hypothetical social media posts. SCRAG can be…
InfoMAE: Pair-Efficient Cross-Modal Alignment for Multimodal Time-Series Sensing Signals
Tomoyoshi Kimura, Xinlin Li, Osama Hanna +10
Standard multimodal self-supervised learning (SSL) algorithms regard cross-modal synchronization as implicit supervisory labels during pretraining, thus posing high requirements on…
Foundation Models for CPS-IoT: Opportunities and Challenges
Ozan Baris, Yizhuo Chen, Gaofeng Dong +9
Methods from machine learning (ML) have transformed the implementation of Perception-Cognition-Communication-Action loops in Cyber-Physical Systems (CPS) and the Internet of Things…
MaSS: Multi-attribute Selective Suppression for Utility-preserving Data Transformation from an Information-theoretic Perspective
Yizhuo Chen, Chun-Fu Chen, Hsiang Hsu +3
The growing richness of large-scale datasets has been crucial in driving the rapid advancement and wide adoption of machine learning technologies. The massive collection and usage…
On the Efficiency and Robustness of Vibration-based Foundation Models for IoT Sensing: A Case Study
Tomoyoshi Kimura, Jinyang Li, Tianshi Wang +9
This paper demonstrates the potential of vibration-based Foundation Models (FMs), pre-trained with unlabeled sensing data, to improve the robustness of run-time inference in (a cla…