3 papers
cs.LG2024
Dependence Induced Representations
Xiangxiang Xu, Lizhong Zheng
We study the problem of learning feature representations from a pair of random variables, where we focus on the representations that are induced by their dependence. We provide suf…
cs.LG2024
Operator SVD with Neural Networks via Nested Low-Rank Approximation
J. Jon Ryu, Xiangxiang Xu, H. S. Melihcan Erol +3
Computing eigenvalue decomposition (EVD) of a given linear operator, or finding its leading eigenvalues and eigenfunctions, is a fundamental task in many machine learning and scien…
cs.LG2024
Neural Feature Learning in Function Space
Xiangxiang Xu, Lizhong Zheng
We present a novel framework for learning system design with neural feature extractors. First, we introduce the feature geometry, which unifies statistical dependence and feature r…