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08/22/2023
Multi-Instance Adversarial Attack on GNN-Based Malicious Domain Detection
Malicious domain detection (MDD) is an open security challenge that aims...
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07/10/2023
Improving Fairness of Graph Neural Networks: A Graph Counterfactual Perspective
Graph neural networks have shown great ability in representation (GNNs) ...
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06/18/2023
Evaluating Graph Neural Networks for Link Prediction: Current Pitfalls and New Benchmarking
Link prediction attempts to predict whether an unseen edge exists based ...
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06/02/2023
Demystifying Structural Disparity in Graph Neural Networks: Can One Size Fit All?
Recent studies on Graph Neural Networks(GNNs) provide both empirical and...
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11/10/2022
Heterogeneous Randomized Response for Differential Privacy in Graph Neural Networks
Graph neural networks (GNNs) are susceptible to privacy inference attack...
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08/30/2022
Learning Representations for Hyper-Relational Knowledge Graphs
Knowledge graphs (KGs) have gained prominence for their ability to learn...
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08/13/2022
Enhancing Graph Contrastive Learning with Node Similarity
Graph Neural Networks (GNNs) have achieved great success in learning gra...
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06/15/2022
Feature Overcorrelation in Deep Graph Neural Networks: A New Perspective
Recent years have witnessed remarkable success achieved by graph neural ...
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05/21/2022
Are Graph Neural Networks Really Helpful for Knowledge Graph Completion?
Knowledge graphs (KGs) facilitate a wide variety of applications due to ...
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04/03/2022
Graph Enhanced BERT for Query Understanding
Query understanding plays a key role in exploring users' search intents ...
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10/18/2021
Hybrid PUF: A Novel Way to Enhance the Security of Classical PUFs
Physical unclonable functions provide a unique 'fingerprint' to a physic...
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09/28/2021
Multimodality in Meta-Learning: A Comprehensive Survey
Meta-learning has gained wide popularity as a training framework that is...
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09/07/2021
QEnclave – A practical solution for secure quantum cloud computing
We introduce a secure hardware device named a QEnclave that can secure t...
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07/05/2021
Elastic Graph Neural Networks
While many existing graph neural networks (GNNs) have been proven to per...
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06/11/2021
Is Homophily a Necessity for Graph Neural Networks?
Graph neural networks (GNNs) have shown great prowess in learning repres...
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06/10/2021
Automated Self-Supervised Learning for Graphs
Graph self-supervised learning has gained increasing attention due to it...
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05/10/2021
Graph Feature Gating Networks
Graph neural networks (GNNs) have received tremendous attention due to t...
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11/19/2020
Node Similarity Preserving Graph Convolutional Networks
Graph Neural Networks (GNNs) have achieved tremendous success in various...
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10/05/2020
A Unified View on Graph Neural Networks as Graph Signal Denoising
Graph Neural Networks (GNNs) have risen to prominence in learning repres...
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05/22/2020
Non-IID Graph Neural Networks
Graph classification is an important task on graph-structured data with ...
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05/20/2020
Graph Structure Learning for Robust Graph Neural Networks
Graph Neural Networks (GNNs) are powerful tools in representation learni...
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05/17/2020
Attacking Black-box Recommendations via Copying Cross-domain User Profiles
Recently, recommender systems that aim to suggest personalized lists of ...
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09/17/2019
Adversarial Attacks and Defenses in Images, Graphs and Text: A Review
Deep neural networks (DNN) have achieved unprecedented success in numero...
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07/16/2019
Deep Social Collaborative Filtering
Recommender systems are crucial to alleviate the information overload pr...
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07/12/2019
R-Transformer: Recurrent Neural Network Enhanced Transformer
Recurrent Neural Networks have long been the dominating choice for seque...
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06/10/2019
Attacking Graph Convolutional Networks via Rewiring
Graph Neural Networks (GNNs) have boosted the performance of many graph ...
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05/30/2019
Deep Adversarial Social Recommendation
Recent years have witnessed rapid developments on social recommendation ...
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04/30/2019
Graph Convolutional Networks with EigenPooling
Graph neural networks, which generalize deep neural network models to gr...
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04/25/2019
Gradient Descent for Sparse Rank-One Matrix Completion for Crowd-Sourced Aggregation of Sparsely Interacting Workers
We consider worker skill estimation for the single-coin Dawid-Skene crow...
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02/19/2019
Graph Neural Networks for Social Recommendation
In recent years, Graph Neural Networks (GNNs), which can naturally integ...
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10/24/2018
Dynamic Graph Neural Networks
Graphs, which describe pairwise relations between objects, are essential...
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09/17/2018
Automata Guided Reinforcement Learning With Demonstrations
Tasks with complex temporal structures and long horizons pose a challeng...
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08/19/2018
Linked Recurrent Neural Networks
Recurrent Neural Networks (RNNs) have been proven to be effective in mod...
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10/31/2017
Automata Guided Hierarchical Reinforcement Learning for Zero-shot Skill Composition
An obstacle that prevents the wide adoption of (deep) reinforcement lear...
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09/27/2017
A Policy Search Method For Temporal Logic Specified Reinforcement Learning Tasks
Reward engineering is an important aspect of reinforcement learning. Whe...
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03/10/2016