61 citations · 66 across the 6 of their papers we have counts for
5 papers · 1 filter
Low-rank Matrix Recovery With Unknown Correspondence
Zhiwei Tang, Tsung-Hui Chang, Xiaojing Ye +1
We study a matrix recovery problem with unknown correspondence: given the observation matrix , where is an unknown permutation matrix, we aim to reco…
Influence Estimation and Maximization via Neural Mean-Field Dynamics
Shushan He, Hongyuan Zha, Xiaojing Ye
We propose a novel learning framework using neural mean-field (NMF) dynamics for inference and estimation problems on heterogeneous diffusion networks. Our new framework leverages…
A Hypergradient Approach to Robust Regression without Correspondence
Yujia Xie, Yixiu Mao, Simiao Zuo +4
We consider a variant of regression problem, where the correspondence between input and output data is not available. Such shuffled data is commonly observed in many real world pro…
Network Diffusions via Neural Mean-Field Dynamics
Shushan He, Hongyuan Zha, Xiaojing Ye
We propose a novel learning framework based on neural mean-field dynamics for inference and estimation problems of diffusion on networks. Our new framework is derived from the Mori…
Wasserstein Learning of Deep Generative Point Process Models
Shuai Xiao, Mehrdad Farajtabar, Xiaojing Ye +3
Point processes are becoming very popular in modeling asynchronous sequential data due to their sound mathematical foundation and strength in modeling a variety of real-world pheno…