6 papers
NeuroLoRA: Context-Aware Neuromodulation for Parameter-Efficient Multi-Task Adaptation
Yuxin Yang, Haoran Zhang, Mingxuan Li +6
Parameter-Efficient Fine-Tuning (PEFT) techniques, particularly Low-Rank Adaptation (LoRA), have become essential for adapting Large Language Models (LLMs) to downstream tasks. Whi…
Statistical Analysis of Conditional Group Distributionally Robust Optimization with Cross-Entropy Loss
Zijian Guo, Zhenyu Wang, Yifan Hu +1
In multi-source learning with discrete labels, distributional heterogeneity across domains poses a central challenge to developing predictive models that transfer reliably to unsee…
StablePCA: Distributionally Robust Learning of Shared Representations from Multi-Source Data
Zhenyu Wang, Molei Liu, Jing Lei +2
When synthesizing multi-source high-dimensional data, a key objective is to extract low-dimensional representations that effectively approximate the original features across differ…
Causal Invariance Learning via Efficient Nonconvex Optimization
Zhenyu Wang, Yifan Hu, Peter Bühlmann +1
Identifying the causal relationship among variables from observational data is an important yet challenging task. This work focuses on identifying the direct causes of an outcome a…
Distributionally Robust Learning for Multi-source Unsupervised Domain Adaptation
Zhenyu Wang, Peter Bühlmann, Zijian Guo
Empirical risk minimization often performs poorly when the distribution of the target domain differs from those of source domains. To address such potential distribution shifts, we…
SIHR: Statistical Inference in High-Dimensional Linear and Logistic Regression Models
Prabrisha Rakshit, Zhenyu Wang, T. Tony Cai +1
We introduce the R package \CRANpkg{SIHR} for statistical inference in high-dimensional generalized linear models with continuous and binary outcomes. The package provides function…