Hongteng Xu

Learning Graphons via Structured Gromov-Wasserstein Barycenters

2021 · Proceedings of the AAAI Conference on Artificial Intelligence

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. Based on the weak regularity lemma from the theory …

Differentiable Hierarchical Optimal Transport for Robust Multi-View Learning

2022 · IEEE Transactions on Pattern Analysis and Machine Intelligence

Traditional multi-view learning methods often rely on two assumptions: ( i) the samples in different views are well-aligned, and ( ii) their representations obey the same distribution in a latent space. Unfortunately, these two assumptions …

Sequential Recommendation with User Memory Networks

2018

User preferences are usually dynamic in real-world recommender systems, and a user»s historical behavior records may not be equally important when predicting his/her future interests. Existing recommendation algorithms -- including both shallow and deep approaches …

Counterfactual Data-Augmented Sequential Recommendation

2021

Sequential recommendation aims at predicting users' preferences based on their historical behaviors. However, this recommendation strategy may not perform well in practice due to the sparsity of the real-world data. In this paper, we propose …