Bayesian Signal Matching for Transfer Learning in ERP-Based Brain Computer Interface [0.03%]
基于ERP的脑计算机接口中转移学习的贝叶斯信号匹配方法研究
Tianwen Ma,Jane E Huggins,Jian Kang
Tianwen Ma
An Event-Related Potential (ERP)-based Brain-Computer Interface (BCI) Speller System assists people with disabilities to communicate by decoding electroencephalogram (EEG) signals. A P300-ERP embedded in EEG signals arises in response to a ...
Tianxi Cai,Mengyan Li,Molei Liu
Tianxi Cai
In this work, we propose a Semi-supervised Triply Robust Inductive transFer LEarning (STRIFLE) approach, which integrates heterogeneous data from a label-rich source population and a label-scarce target population and utilizes a large amoun...
Ye Tian,Yang Feng
Ye Tian
In this work, we study the transfer learning problem under highdimensional generalized linear models (GLMs), which aim to improve the fit on target data by borrowing information from useful source data. Given which sources to transfer, we p...
Accommodating time-varying heterogeneity in risk estimation under the Cox model: a transfer learning approach [0.03%]
Cox模型下的风险估计中适应时变异质性的迁移学习方法研究
Ziyi Li,Yu Shen,Jing Ning
Ziyi Li
Transfer learning has attracted increasing attention in recent years for adaptively borrowing information across different data cohorts in various settings. Cancer registries have been widely used in clinical research because of their easy ...
Transfer Learning in Large-scale Gaussian Graphical Models with False Discovery Rate Control [0.03%]
大规模高斯图形模型中带假发现率控制的变换学习
Sai Li,T Tony Cai,Hongzhe Li
Sai Li
Transfer learning for high-dimensional Gaussian graphical models (GGMs) is studied. The target GGM is estimated by incorporating the data from similar and related auxiliary studies, where the similarity between the target graph and each aux...