4 papers
Federated LoRA Fine-Tuning for LLMs via Collaborative Alignment
Shuaida He, Liwen Chen, Long Feng
Low-rank adaptation (LoRA) has emerged as a powerful tool for parameter-efficient fine-tuning of large language models (LLMs). This paper studies LoRA under a federated learning se…
Large-Scale Asset Selection via Metric Dependence with Enriched High Frequency Information
Yangzhou Chen, Shuaida He, Xin Chen
Large-scale portfolio choice is highly sensitive to estimation error, making the preliminary asset selection essential in empirical implementation. Existing selection rules typical…
Large-scale metric objects filtering for binary classification with application to abnormal brain connectivity detection
Shuaida He, Jiaqi Li, Xin Chen
The classification of random objects within metric spaces without a vector structure has attracted increasing attention. However, the complexity inherent in such non-Euclidean data…
High-Dimensional Sparse Single-Index Regression Via Hilbert-Schmidt Independence Criterion
Runxiong Wu, Chang Deng, Xin Chen
Hilbert-Schmidt Independence Criterion (HSIC) has recently been used in the field of single-index models to estimate the directions. Compared with some other well-established metho…