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09/02/2023
Bias and Fairness in Large Language Models: A Survey
Rapid advancements of large language models (LLMs) have enabled the proc...
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07/08/2023
Fairness-Aware Graph Neural Networks: A Survey
Graph Neural Networks (GNNs) have become increasingly important due to t...
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05/09/2023
Learning to Parallelize with OpenMP by Augmented Heterogeneous AST Representation
Detecting parallelizable code regions is a challenging task, even for ex...
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03/07/2023
Neural Compositional Rule Learning for Knowledge Graph Reasoning
Learning logical rules is critical to improving reasoning in KGs. This i...
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12/22/2022
Graph Learning with Localized Neighborhood Fairness
Learning fair graph representations for downstream applications is becom...
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09/22/2022
Memory-Augmented Graph Neural Networks: A Neuroscience Perspective
Graph neural networks (GNNs) have been extensively used for many domains...
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04/25/2022
End-to-end Mapping in Heterogeneous Systems Using Graph Representation Learning
To enable heterogeneous computing systems with autonomous programming an...
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01/22/2022
Joint Learning of Hierarchical Community Structure and Node Representations: An Unsupervised Approach
Graph representation learning has demonstrated improved performance in t...
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04/14/2021
DistGNN: Scalable Distributed Training for Large-Scale Graph Neural Networks
Full-batch training on Graph Neural Networks (GNN) to learn the structur...
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02/12/2021
Personalized Visualization Recommendation
Visualization recommendation work has focused solely on scoring visualiz...
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10/23/2020
Heterogeneous Graphlets
In this paper, we introduce a generalization of graphlets to heterogeneo...
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10/13/2020
PIUMA: Programmable Integrated Unified Memory Architecture
High performance large scale graph analytics is essential to timely anal...
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10/09/2020
A Vertex Cut based Framework for Load Balancing and Parallelism Optimization in Multi-core Systems
High-level applications, such as machine learning, are evolving from sim...
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09/28/2020
Graph Neural Networks with Heterophily
Graph Neural Networks (GNNs) have proven to be useful for many different...
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12/25/2019
Deep Graph Similarity Learning: A Survey
In many domains where data are represented as graphs, learning a similar...
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10/18/2019
Temporal Network Sampling
Temporal networks representing a stream of timestamped edges are seeming...
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09/20/2019
NeuroVectorizer: End-to-End Vectorization with Deep Reinforcement Learning
One of the key challenges arising when compilers vectorize loops for tod...
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08/22/2019
From Community to Role-based Graph Embeddings
Roles are sets of structurally similar nodes that are more similar to no...
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08/04/2019
Deep Reinforcement Learning in System Optimization
The recent advancements in deep reinforcement learning have opened new h...
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08/02/2019
Network Shrinkage Estimation
Networks are a natural representation of complex systems across the scie...
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06/14/2019
Linear-time Hierarchical Community Detection
Community detection in graphs has many important and fundamental applica...
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06/12/2019
Higher-Order Ranking and Link Prediction: From Closing Triangles to Closing Higher-Order Motifs
In this paper, we introduce the notion of motif closure and describe hig...
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04/12/2019
Temporal Network Representation Learning
Networks evolve continuously over time with the addition, deletion, and ...
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01/28/2019
Heterogeneous Network Motifs
Many real-world applications give rise to large heterogeneous networks w...
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11/02/2018
Similarity Learning with Higher-Order Proximity for Brain Network Analysis
In recent years, the similarity learning problem has been widely studied...
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07/20/2018
Attention Models in Graphs: A Survey
Graph-structured data arise naturally in many different application doma...
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05/07/2018
Predicting Graph Categories from Structural Properties
Complex networks are often categorized according to the underlying pheno...
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02/07/2018
Learning Role-based Graph Embeddings
Random walks are at the heart of many existing network embedding methods...
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01/28/2018
HONE: Higher-Order Network Embeddings
This paper describes a general framework for learning Higher-Order Netwo...
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12/22/2017
Estimating Node Similarity by Sampling Streaming Bipartite Graphs
Bipartite graph data increasingly occurs as a stream of edges that repre...
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10/27/2017
Similarity-based Multi-label Learning
Multi-label classification is an important learning problem with many ap...
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10/25/2017
Inductive Representation Learning in Large Attributed Graphs
Graphs (networks) are ubiquitous and allow us to model entities (nodes) ...
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09/14/2017
A Framework for Generalizing Graph-based Representation Learning Methods
Random walks are at the heart of many existing deep learning algorithms ...
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09/13/2017
Network Classification and Categorization
To the best of our knowledge, this paper presents the first large-scale ...
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04/28/2017
Deep Feature Learning for Graphs
This paper presents a general graph representation learning framework ca...
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01/06/2017
Estimation of Graphlet Statistics
Graphlets are induced subgraphs of a large network and are important for...
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10/04/2016
Revisiting Role Discovery in Networks: From Node to Edge Roles
Previous work in network analysis has focused on modeling the mixed-memb...
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08/02/2016
Relational Similarity Machines
This paper proposes Relational Similarity Machines (RSM): a fast, accura...
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06/13/2015
Graphlet Decomposition: Framework, Algorithms, and Applications
From social science to biology, numerous applications often rely on grap...
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02/02/2015
A Web-based Interactive Visual Graph Analytics Platform
This paper proposes a web-based visual graph analytics platform for inte...
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03/14/2014
Learning the Latent State Space of Time-Varying Graphs
From social networks to Internet applications, a wide variety of electro...
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11/14/2012
