6 papers
Diagonalized Attention for Individualized Regression: Latent-Row Localization and Prediction
Borui Peng, Liwei Lin, Feifei Wang +1
Modern text and image representations are often matrix-valued, with rows corresponding to tokens, patches, or other local feature vectors. Predictive information is often sparse bu…
Semi-Supervised Generative Learning via Latent Space Distribution Matching
Kwong Yu Chong, Long Feng
We introduce Latent Space Distribution Matching (LSDM), a novel framework for semi-supervised generative modeling of conditional distributions. LSDM operates in two stages: (i) lea…
Nonlinear Multiple Response Regression and Learning of Latent Spaces
Ye Tian, Sanyou Wu, Long Feng
Identifying low-dimensional latent structures within high-dimensional data has long been a central topic in the machine learning community, driven by the need for data compression,…
Sparsity-Induced Global Matrix Autoregressive Model with Auxiliary Network Data
Sanyou Wu, Dan Yang, Yan Xu +1
Jointly modeling and forecasting economic and financial variables across a large set of countries has long been a significant challenge. Two primary approaches have been utilized t…
A General Framework of Brain Region Detection And Genetic Variants Selection in Imaging Genetics
Siqiang Su, Zhenghao Li, Long Feng +1
Imaging genetics is a growing field that employs structural or functional neuroimaging techniques to study individuals with genetic risk variants potentially linked to specific ill…
Time Series Generative Learning with Application to Brain Imaging Analysis
Zhenghao Li, Sanyou Wu, Long Feng
This paper focuses on the analysis of sequential image data, particularly brain imaging data such as MRI, fMRI, CT, with the motivation of understanding the brain aging process and…