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20162023
most citedGromov-Wasserstein Learning for Graph Matching and Node Embedding

88 citations · 223 across the 16 of their papers we have counts for

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Showing 2018Show all

6 papers · 1 filter

cs.LG2018

PoPPy: A Point Process Toolbox Based on PyTorch

Hongteng Xu

PoPPy is a Point Process toolbox based on PyTorch, which achieves flexible designing and efficient learning of point process models. It can be used for interpretable sequential dat…

cs.LG2018

Distilled Wasserstein Learning for Word Embedding and Topic Modeling

Hongteng Xu, Wenlin Wang, Wei Liu +1

We propose a novel Wasserstein method with a distillation mechanism, yielding joint learning of word embeddings and topics. The proposed method is based on the fact that the Euclid…

stat.ML2018

Predicting Smoking Events with a Time-Varying Semi-Parametric Hawkes Process Model

Matthew Engelhard, Hongteng Xu, Lawrence Carin +3

Health risks from cigarette smoking -- the leading cause of preventable death in the United States -- can be substantially reduced by quitting. Although most smokers are motivated…

eess.IV2018

Learning an Inverse Tone Mapping Network with a Generative Adversarial Regularizer

Shiyu Ning, Hongteng Xu, Li Song +2

Transferring a low-dynamic-range (LDR) image to a high-dynamic-range (HDR) image, which is the so-called inverse tone mapping (iTM), is an important imaging technique to improve vi…

stat.ML2018

Superposition-Assisted Stochastic Optimization for Hawkes Processes

Hongteng Xu, Xu Chen, Lawrence Carin

We consider the learning of multi-agent Hawkes processes, a model containing multiple Hawkes processes with shared endogenous impact functions and different exogenous intensities.…

cs.IR2018★ 44 cited

Visually Explainable Recommendation

Xu Chen, Yongfeng Zhang, Hongteng Xu +3

Images account for a significant part of user decisions in many application scenarios, such as product images in e-commerce, or user image posts in social networks. It is intuitive…