
Universal Representation Learning of Knowledge Bases by Jointly Embedding Instances and Ontological Concepts
Many largescale knowledge bases simultaneously represent two views of k...
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BioJOIE: Joint Representation Learning of Biological Knowledge Bases
The widespread of Coronavirus has led to a worldwide pandemic with a hig...
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CREATe: Clinical Report Extraction and Annotation Technology
Clinical case reports are written descriptions of the unique aspects of ...
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MotifDriven Contrastive Learning of Graph Representations
Graph motifs are significant subgraph patterns occurring frequently in g...
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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...
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Queryfree Blackbox Adversarial Attacks on Graphs
Many graphbased machine learning models are known to be vulnerable to a...
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Unsupervised AdversariallyRobust Representation Learning on Graphs
Recent works have demonstrated that deep learning on graphs is vulnerabl...
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Learning Continuous System Dynamics from IrregularlySampled Partial Observations
Many realworld systems, such as moving planets, can be considered as mu...
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Multivariate Time Series Classification with Hierarchical Variational Graph Pooling
Over the past decade, multivariate time series classification (MTSC) has...
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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 ...
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GPTGNN: Generative PreTraining of Graph Neural Networks
Graph neural networks (GNNs) have been demonstrated to be powerful in mo...
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BiLevel Graph Neural Networks for DrugDrug Interaction Prediction
We introduce BiGNN for modeling biological link prediction tasks such a...
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TIMME: Twitter Ideologydetection via Multitask Multirelational Embedding
We aim at solving the problem of predicting people's ideology, or politi...
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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...
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Software Language Comprehension using a ProgramDerived Semantic Graph
Traditional code transformation structures, such as an abstract syntax t...
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Heterogeneous Network Representation Learning: Survey, Benchmark, Evaluation, and Beyond
Since realworld objects and their interactions are often multimodal an...
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Heterogeneous Graph Transformer
Recent years have witnessed the emerging success of graph neural network...
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Fast Detection of Maximum Common Subgraph via Deep QLearning
Detecting the Maximum Common Subgraph (MCS) between two input graphs is ...
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LayerDependent Importance Sampling for Training Deep and Large Graph Convolutional Networks
Graph convolutional networks (GCNs) have recently received wide attentio...
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Differentiable Product Quantization for EndtoEnd Embedding Compression
Embedding layer is commonly used to map discrete symbols into continuous...
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FewShot Representation Learning for OutOfVocabulary Words
Existing approaches for learning word embeddings often assume there are ...
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PreTraining Graph Neural Networks for Generic Structural Feature Extraction
Graph neural networks (GNNs) are shown to be successful in modeling appl...
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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 ...
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Dissecting Graph Neural Networks on Graph Classification
Graph Neural Nets (GNNs) have received increasing attentions, partially ...
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Learning Fair Representations via an Adversarial Framework
Fairness has become a central issue for our research community as classi...
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Unsupervised Inductive WholeGraph Embedding by Preserving Graph Proximity
We introduce a novel approach to graphlevel representation learning, wh...
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Embedding Uncertain Knowledge Graphs
Embedding models for deterministic Knowledge Graphs (KG) have been exten...
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Convolutional Set Matching for Graph Similarity
We introduce GSimCNN (Graph Similarity Computation via Convolutional Neu...
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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...
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Graph Edit Distance Computation via Graph Neural Networks
Graph similarity search is among the most important graphbased applicat...
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The Art of Drafting: A TeamOriented Hero Recommendation System for Multiplayer Online Battle Arena Games
Multiplayer Online Battle Arena (MOBA) games have received increasing po...
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QDeckRec: A Fast Deck Recommendation System for Collectible Card Games
Deck building is a crucial component in playing Collectible Card Games (...
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Learning Kway Ddimensional Discrete Codes for Compact Embedding Representations
Conventional embedding methods directly associate each symbol with a con...
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HeteroMed: Heterogeneous Information Network for Medical Diagnosis
With the recent availability of Electronic Health Records (EHR) and grea...
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A SemanticRich Similarity Measure in Heterogeneous Information Networks
Measuring the similarities between objects in information networks has f...
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Recurrent MetaStructure for Robust Similarity Measure in Heterogeneous Information Networks
Similarity measure as a fundamental task in heterogeneous information ne...
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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...
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Learning Kway Ddimensional Discrete Code For Compact Embedding Representations
Embedding methods such as word embedding have become pillars for many ap...
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On Sampling Strategies for Neural Networkbased Collaborative Filtering
Recent advances in neural networks have inspired people to design hybrid...
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Joint Text Embedding for Personalized Contentbased Recommendation
Learning a good representation of text is key to many recommendation app...
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Player Skill Decomposition in Multiplayer Online Battle Arenas
Successful analysis of player skills in video games has important impact...
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TaskGuided and PathAugmented Heterogeneous Network Embedding for Author Identification
In this paper, we study the problem of author identification under doubl...
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Entity Embeddingbased Anomaly Detection for Heterogeneous Categorical Events
Anomaly detection plays an important role in modern datadriven security...
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Yizhou Sun
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