3 citations · 7 across the 13 of their papers we have counts for
8 papers · 1 filter
Train Smarter, Not Longer: Memorization-Guided Data Reuse for Efficient LLM Training
Jingwei Zuo, Cong Zeng, Ilyas Chahed +6
The training paradigm of large language models has shifted from traditional one-pass training to multi-epoch training, as reasonable reuse of limited high-quality data can improve…
Learnable Multipliers: Freeing the Scale of Language Model Matrix Layers
Maksim Velikanov, Ilyas Chahed, Jingwei Zuo +3
Applying weight decay (WD) to matrix layers is standard practice in large-language-model pretraining. Prior work suggests that stochastic gradient noise induces a Brownian-like exp…
MAGNETO: Edge AI for Human Activity Recognition -- Privacy and Personalization
Jingwei Zuo, George Arvanitakis, Mthandazo Ndhlovu +1
Human activity recognition (HAR) is a well-established field, significantly advanced by modern machine learning (ML) techniques. While companies have successfully integrated HAR in…
Opportunistic Air Quality Monitoring and Forecasting with Expandable Graph Neural Networks
Jingwei Zuo, Wenbin Li, Michele Baldo +1
Air Quality Monitoring and Forecasting has been a popular research topic in recent years. Recently, data-driven approaches for air quality forecasting have garnered significant att…
Unleashing Realistic Air Quality Forecasting: Introducing the Ready-to-Use PurpleAirSF Dataset
Jingwei Zuo, Wenbin Li, Michele Baldo +1
Air quality forecasting has garnered significant attention recently, with data-driven models taking center stage due to advancements in machine learning and deep learning models. H…
On Handling Catastrophic Forgetting for Incremental Learning of Human Physical Activity on the Edge
Jingwei Zuo, George Arvanitakis, Hakim Hacid
Human activity recognition (HAR) has been a classic research problem. In particular, with recent machine learning (ML) techniques, the recognition task has been largely investigate…
Graph Convolutional Networks for Traffic Forecasting with Missing Values
Jingwei Zuo, Karine Zeitouni, Yehia Taher +1
Traffic forecasting has attracted widespread attention recently. In reality, traffic data usually contains missing values due to sensor or communication errors. The Spatio-temporal…
SMATE: Semi-Supervised Spatio-Temporal Representation Learning on Multivariate Time Series
Jingwei Zuo, Karine Zeitouni, Yehia Taher
Learning from Multivariate Time Series (MTS) has attracted widespread attention in recent years. In particular, label shortage is a real challenge for the classification task on MT…