199 citations · 203 across the 10 of their papers we have counts for
11 papers
CF-LoRA: Decoupled Factor Aggregation and Adaptation-Aware Client Clustering for Federated LoRA Fine-Tuning
Mengjun Yi, Langxing Yang, Suhan Guo +2
Federated LoRA fine-tuning enables parameter-efficient adaptation of pre-trained models without sharing private data, but suffers from two fundamental mismatches under heterogeneou…
T-LLM: Teaching Large Language Models to Forecast Time Series via Temporal Distillation
Suhan Guo, Bingxu Wang, Shaodan Zhang +1
Time series forecasting plays a critical role in decision-making across many real-world applications. Unlike data in vision and language domains, time series data is inherently tie…
MiCA: A Mobility-Informed Causal Adapter for Lightweight Epidemic Forecasting
Suhan Guo, Jiahong Deng, Furao Shen
Accurate forecasting of infectious disease dynamics is critical for public health planning and intervention. Human mobility plays a central role in shaping the spatial spread of ep…
IPF-RDA: An Information-Preserving Framework for Robust Data Augmentation
Suorong Yang, Hongchao Yang, Suhan Guo +2
Data augmentation is widely utilized as an effective technique to enhance the generalization performance of deep models. However, data augmentation may inevitably introduce distrib…
Enhancing Epidemic Forecasting: Evaluating the Role of Mobility Data and Graph Convolutional Networks
Suhan Guo, Zhenghao Xu, Furao Shen +1
Accurate prediction of contagious disease outbreaks is vital for informed decision-making. Our study addresses the gap between machine learning algorithms and their epidemiological…
SPAT: Sensitivity-based Multihead-attention Pruning on Time Series Forecasting Models
Suhan Guo, Jiahong Deng, Mengjun Yi +2
Attention-based architectures have achieved superior performance in multivariate time series forecasting but are computationally expensive. Techniques such as patching and adaptive…
Estimating the treatment effect over time under general interference through deep learner integrated TMLE
Suhan Guo, Furao Shen, Ni Li
Understanding the effects of quarantine policies in populations with underlying social networks is crucial for public health, yet most causal inference methods fail here due to the…
RAM: Replace Attention with MLP for Efficient Multivariate Time Series Forecasting
Suhan Guo, Jiahong Deng, Yi Wei +3
Attention-based architectures have become ubiquitous in time series forecasting tasks, including spatio-temporal (STF) and long-term time series forecasting (LTSF). Yet, our unders…
Multi-Scale Dilated Convolution Network for Long-Term Time Series Forecasting
Feifei Li, Suhan Guo, Feng Han +2
Accurate forecasting of long-term time series has important applications for decision making and planning. However, it remains challenging to capture the long-term dependencies in…
Not All Data Matters: An End-to-End Adaptive Dataset Pruning Framework for Enhancing Model Performance and Efficiency
Suorong Yang, Hongchao Yang, Suhan Guo +2
While deep neural networks have demonstrated remarkable performance across various tasks, they typically require massive training data. Due to the presence of redundancies and bias…
Image Data Augmentation for Deep Learning: A Survey
Suorong Yang, Weikang Xiao, Mengchen Zhang +3
Deep learning has achieved remarkable results in many computer vision tasks. Deep neural networks typically rely on large amounts of training data to avoid overfitting. However, la…