b'Yizhou Sun'

Motif-Driven Contrastive Learning of Graph Representations

Graph motifs are significant subgraph patterns occurring frequently in g...
12/23/2020 ∙ by Shichang Zhang, et al. ∙ 0 ∙ share

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Clinical Temporal Relation Extraction with Probabilistic Soft Logic Regularization and Global Inference

There has been a steady need in the medical community to precisely extra...
12/16/2020 ∙ by Yichao Zhou, et al. ∙ 11 ∙ share

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Query-free Black-box Adversarial Attacks on Graphs

Many graph-based machine learning models are known to be vulnerable to a...
12/12/2020 ∙ by Jiarong Xu, et al. ∙ 0 ∙ share

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Unsupervised Adversarially-Robust Representation Learning on Graphs

Recent works have demonstrated that deep learning on graphs is vulnerabl...
12/04/2020 ∙ by Jiarong Xu, et al. ∙ 0 ∙ share

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Learning Continuous System Dynamics from Irregularly-Sampled Partial Observations

Many real-world systems, such as moving planets, can be considered as mu...
11/08/2020 ∙ by Zijie Huang, et al. ∙ 0 ∙ share

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Multivariate Time Series Classification with Hierarchical Variational Graph Pooling

Over the past decade, multivariate time series classification (MTSC) has...
10/12/2020 ∙ by Haoyan Xu, et al. ∙ 4 ∙ share

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Multilingual Knowledge Graph Completion via Ensemble Knowledge Transfer

Predicting missing facts in a knowledge graph (KG) is a crucial task in ...
10/07/2020 ∙ by Xuelu Chen, et al. ∙ 21 ∙ share

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GPT-GNN: Generative Pre-Training of Graph Neural Networks

Graph neural networks (GNNs) have been demonstrated to be powerful in mo...
06/27/2020 ∙ by Ziniu Hu, et al. ∙ 43 ∙ share

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Bi-Level Graph Neural Networks for Drug-Drug Interaction Prediction

We introduce Bi-GNN for modeling biological link prediction tasks such a...
06/11/2020 ∙ by Yunsheng Bai, et al. ∙ 0 ∙ share

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TIMME: Twitter Ideology-detection via Multi-task Multi-relational Embedding

We aim at solving the problem of predicting people's ideology, or politi...
06/02/2020 ∙ by Zhiping Xiao, et al. ∙ 18 ∙ share

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Hierarchical and Fast Graph Similarity Computation via Graph Coarsening and Deep Graph Learning

In this work, we are interested in the large graph similarity computatio...
05/14/2020 ∙ by Haoyan Xu, et al. ∙ 5 ∙ share

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Software Language Comprehension using a Program-Derived Semantic Graph

Traditional code transformation structures, such as an abstract syntax t...
04/02/2020 ∙ by Roshni G. Iyer, et al. ∙ 1 ∙ share

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Heterogeneous Network Representation Learning: Survey, Benchmark, Evaluation, and Beyond

Since real-world objects and their interactions are often multi-modal an...
04/01/2020 ∙ by Carl Yang, et al. ∙ 0 ∙ share

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Heterogeneous Graph Transformer

Recent years have witnessed the emerging success of graph neural network...
03/03/2020 ∙ by Ziniu Hu, et al. ∙ 0 ∙ share

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Fast Detection of Maximum Common Subgraph via Deep Q-Learning

Detecting the Maximum Common Subgraph (MCS) between two input graphs is ...
02/08/2020 ∙ by Yunsheng Bai, et al. ∙ 22 ∙ share

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Layer-Dependent Importance Sampling for Training Deep and Large Graph Convolutional Networks

Graph convolutional networks (GCNs) have recently received wide attentio...
11/17/2019 ∙ by Difan Zou, et al. ∙ 10 ∙ share

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Differentiable Product Quantization for End-to-End Embedding Compression

Embedding layer is commonly used to map discrete symbols into continuous...
08/26/2019 ∙ by Ting Chen, et al. ∙ 4 ∙ share

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Few-Shot Representation Learning for Out-Of-Vocabulary Words

Existing approaches for learning word embeddings often assume there are ...
07/01/2019 ∙ by Ziniu Hu, et al. ∙ 0 ∙ share

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Pre-Training Graph Neural Networks for Generic Structural Feature Extraction

Graph neural networks (GNNs) are shown to be successful in modeling appl...
05/31/2019 ∙ by Ziniu Hu, et al. ∙ 2 ∙ share

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Learning to Identify High Betweenness Centrality Nodes from Scratch: A Novel Graph Neural Network Approach

Betweenness centrality (BC) is one of the most used centrality measures ...
05/24/2019 ∙ by Changjun Fan, et al. ∙ 0 ∙ share

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Dissecting Graph Neural Networks on Graph Classification

Graph Neural Nets (GNNs) have received increasing attentions, partially ...
05/11/2019 ∙ by Ting Chen, et al. ∙ 0 ∙ share

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Learning Fair Representations via an Adversarial Framework

Fairness has become a central issue for our research community as classi...
04/30/2019 ∙ by Rui Feng, et al. ∙ 0 ∙ share

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Unsupervised Inductive Whole-Graph Embedding by Preserving Graph Proximity

We introduce a novel approach to graph-level representation learning, wh...
04/01/2019 ∙ by Yunsheng Bai, et al. ∙ 0 ∙ share

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Embedding Uncertain Knowledge Graphs

Embedding models for deterministic Knowledge Graphs (KG) have been exten...
11/26/2018 ∙ by Xuelu Chen, et al. ∙ 0 ∙ share

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Convolutional Set Matching for Graph Similarity

We introduce GSimCNN (Graph Similarity Computation via Convolutional Neu...
10/23/2018 ∙ by Yunsheng Bai, et al. ∙ 2 ∙ share

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Convolutional Neural Networks for Fast Approximation of Graph Edit Distance

Graph Edit Distance (GED) computation is a core operation of many widely...
09/10/2018 ∙ by Yunsheng Bai, et al. ∙ 0 ∙ share

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Graph Edit Distance Computation via Graph Neural Networks

Graph similarity search is among the most important graph-based applicat...
08/16/2018 ∙ by Yunsheng Bai, et al. ∙ 0 ∙ share

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The Art of Drafting: A Team-Oriented Hero Recommendation System for Multiplayer Online Battle Arena Games

Multiplayer Online Battle Arena (MOBA) games have received increasing po...
06/26/2018 ∙ by Zhengxing Chen, et al. ∙ 0 ∙ share

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Q-DeckRec: A Fast Deck Recommendation System for Collectible Card Games

Deck building is a crucial component in playing Collectible Card Games (...
06/26/2018 ∙ by Zhengxing Chen, et al. ∙ 0 ∙ share

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Learning K-way D-dimensional Discrete Codes for Compact Embedding Representations

Conventional embedding methods directly associate each symbol with a con...
06/21/2018 ∙ by Ting Chen, et al. ∙ 0 ∙ share

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HeteroMed: Heterogeneous Information Network for Medical Diagnosis

With the recent availability of Electronic Health Records (EHR) and grea...
04/22/2018 ∙ by Anahita Hosseini, et al. ∙ 0 ∙ share

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A Semantic-Rich Similarity Measure in Heterogeneous Information Networks

Measuring the similarities between objects in information networks has f...
01/02/2018 ∙ by Yu Zhou, et al. ∙ 0 ∙ share

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Recurrent Meta-Structure for Robust Similarity Measure in Heterogeneous Information Networks

Similarity measure as a fundamental task in heterogeneous information ne...
12/25/2017 ∙ by Yu Zhou, et al. ∙ 0 ∙ share

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DMSS: A Robust Deep Meta Structure Based Similarity Measure in Heterogeneous Information Networks

Similarity measure as a fundamental task in heterogeneous information ne...
12/25/2017 ∙ by Yu Zhou, et al. ∙ 0 ∙ share

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Learning K-way D-dimensional Discrete Code For Compact Embedding Representations

Embedding methods such as word embedding have become pillars for many ap...
11/08/2017 ∙ by Ting Chen, et al. ∙ 0 ∙ share

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On Sampling Strategies for Neural Network-based Collaborative Filtering

Recent advances in neural networks have inspired people to design hybrid...
06/23/2017 ∙ by Ting Chen, et al. ∙ 0 ∙ share

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Joint Text Embedding for Personalized Content-based Recommendation

Learning a good representation of text is key to many recommendation app...
06/04/2017 ∙ by Ting Chen, et al. ∙ 0 ∙ share

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Player Skill Decomposition in Multiplayer Online Battle Arenas

Successful analysis of player skills in video games has important impact...
02/21/2017 ∙ by Zhengxing Chen, et al. ∙ 0 ∙ share

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Task-Guided and Path-Augmented Heterogeneous Network Embedding for Author Identification

In this paper, we study the problem of author identification under doubl...
12/08/2016 ∙ by Ting Chen, et al. ∙ 0 ∙ share

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Entity Embedding-based Anomaly Detection for Heterogeneous Categorical Events

Anomaly detection plays an important role in modern data-driven security...
08/26/2016 ∙ by Ting Chen, et al. ∙ 0 ∙ share

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Yizhou Sun

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