5 citations · 7 across the 6 of their papers we have counts for
6 papers
Causal Discovery from Subsampled Time Series with Proxy Variables
Mingzhou Liu, Xinwei Sun, Lingjing Hu +1
Inferring causal structures from time series data is the central interest of many scientific inquiries. A major barrier to such inference is the problem of subsampling, i.e., the f…
Leveraging both Lesion Features and Procedural Bias in Neuroimaging: An Dual-Task Split dynamics of inverse scale space
Xinwei Sun, Wenjing Han, Lingjing Hu +2
The prediction and selection of lesion features are two important tasks in voxel-based neuroimage analysis. Existing multivariate learning models take two tasks equivalently and op…
TCGM: An Information-Theoretic Framework for Semi-Supervised Multi-Modality Learning
Xinwei Sun, Yilun Xu, Peng Cao +4
Fusing data from multiple modalities provides more information to train machine learning systems. However, it is prohibitively expensive and time-consuming to label each modality w…
FDR-HS: An Empirical Bayesian Identification of Heterogenous Features in Neuroimage Analysis
Xinwei Sun, Lingjing Hu, Fandong Zhang +2
Recent studies found that in voxel-based neuroimage analysis, detecting and differentiating "procedural bias" that are introduced during the preprocessing steps from lesion feature…
GSplit LBI: Taming the Procedural Bias in Neuroimaging for Disease Prediction
Xinwei Sun, Lingjing Hu, Yuan Yao +1
In voxel-based neuroimage analysis, lesion features have been the main focus in disease prediction due to their interpretability with respect to the related diseases. However, we o…
Stable Feature Selection from Brain sMRI
Bo Xin, Lingjing Hu, Yizhou Wang +1
Neuroimage analysis usually involves learning thousands or even millions of variables using only a limited number of samples. In this regard, sparse models, e.g. the lasso, are app…