
DistGNN: Scalable Distributed Training for LargeScale Graph Neural Networks
Fullbatch training on Graph Neural Networks (GNN) to learn the structur...
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Personalized Visualization Recommendation
Visualization recommendation work has focused solely on scoring visualiz...
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Heterogeneous Graphlets
In this paper, we introduce a generalization of graphlets to heterogeneo...
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PIUMA: Programmable Integrated Unified Memory Architecture
High performance large scale graph analytics is essential to timely anal...
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A Vertex Cut based Framework for Load Balancing and Parallelism Optimization in Multicore Systems
Highlevel applications, such as machine learning, are evolving from sim...
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Graph Neural Networks with Heterophily
Graph Neural Networks (GNNs) have proven to be useful for many different...
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Deep Graph Similarity Learning: A Survey
In many domains where data are represented as graphs, learning a similar...
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Temporal Network Sampling
Temporal networks representing a stream of timestamped edges are seeming...
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NeuroVectorizer: EndtoEnd Vectorization with Deep Reinforcement Learning
One of the key challenges arising when compilers vectorize loops for tod...
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From Community to Rolebased Graph Embeddings
Roles are sets of structurally similar nodes that are more similar to no...
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Deep Reinforcement Learning in System Optimization
The recent advancements in deep reinforcement learning have opened new h...
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Network Shrinkage Estimation
Networks are a natural representation of complex systems across the scie...
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Lineartime Hierarchical Community Detection
Community detection in graphs has many important and fundamental applica...
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HigherOrder Ranking and Link Prediction: From Closing Triangles to Closing HigherOrder Motifs
In this paper, we introduce the notion of motif closure and describe hig...
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Temporal Network Representation Learning
Networks evolve continuously over time with the addition, deletion, and ...
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Heterogeneous Network Motifs
Many realworld applications give rise to large heterogeneous networks w...
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Similarity Learning with HigherOrder Proximity for Brain Network Analysis
In recent years, the similarity learning problem has been widely studied...
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Attention Models in Graphs: A Survey
Graphstructured data arise naturally in many different application doma...
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Predicting Graph Categories from Structural Properties
Complex networks are often categorized according to the underlying pheno...
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Learning Rolebased Graph Embeddings
Random walks are at the heart of many existing network embedding methods...
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HONE: HigherOrder Network Embeddings
This paper describes a general framework for learning HigherOrder Netwo...
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Estimating Node Similarity by Sampling Streaming Bipartite Graphs
Bipartite graph data increasingly occurs as a stream of edges that repre...
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Similaritybased Multilabel Learning
Multilabel classification is an important learning problem with many ap...
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Inductive Representation Learning in Large Attributed Graphs
Graphs (networks) are ubiquitous and allow us to model entities (nodes) ...
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A Framework for Generalizing Graphbased Representation Learning Methods
Random walks are at the heart of many existing deep learning algorithms ...
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Network Classification and Categorization
To the best of our knowledge, this paper presents the first largescale ...
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Deep Feature Learning for Graphs
This paper presents a general graph representation learning framework ca...
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Estimation of Graphlet Statistics
Graphlets are induced subgraphs of a large network and are important for...
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Revisiting Role Discovery in Networks: From Node to Edge Roles
Previous work in network analysis has focused on modeling the mixedmemb...
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Relational Similarity Machines
This paper proposes Relational Similarity Machines (RSM): a fast, accura...
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Graphlet Decomposition: Framework, Algorithms, and Applications
From social science to biology, numerous applications often rely on grap...
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A Webbased Interactive Visual Graph Analytics Platform
This paper proposes a webbased visual graph analytics platform for inte...
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Learning the Latent State Space of TimeVarying Graphs
From social networks to Internet applications, a wide variety of electro...
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Network Sampling: From Static to Streaming Graphs
Network sampling is integral to the analysis of social, information, and...
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