88 citations · 219 across the 15 of their papers we have counts for
25 papers
Interventional Multi-Instance Learning with Deconfounded Instance-Level Prediction
Tiancheng Lin, Hongteng Xu, Canqian Yang +1
When applying multi-instance learning (MIL) to make predictions for bags of instances, the prediction accuracy of an instance often depends on not only the instance itself but also…
Hawkes Processes on Graphons
Hongteng Xu, Dixin Luo, Hongyuan Zha
We propose a novel framework for modeling multiple multivariate point processes, each with heterogeneous event types that share an underlying space and obey the same generative mec…
Learning Graphons via Structured Gromov-Wasserstein Barycenters
Hongteng Xu, Dixin Luo, Lawrence Carin +1
We propose a novel and principled method to learn a nonparametric graph model called graphon, which is defined in an infinite-dimensional space and represents arbitrary-size graphs…
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…
Hierarchical Optimal Transport for Robust Multi-View Learning
Dixin Luo, Hongteng Xu, Lawrence Carin
Traditional multi-view learning methods often rely on two assumptions: () the samples in different views are well-aligned, and () their representations in latent space obey…
Learning Autoencoders with Relational Regularization
Hongteng Xu, Dixin Luo, Ricardo Henao +2
A new algorithmic framework is proposed for learning autoencoders of data distributions. We minimize the discrepancy between the model and target distributions, with a \emph{relati…