b'Yao Ma'

research

∙ 08/22/2023

Multi-Instance Adversarial Attack on GNN-Based Malicious Domain Detection

Malicious domain detection (MDD) is an open security challenge that aims...

0 Mahmoud Nazzal, et al. ∙

research

∙ 07/10/2023

Improving Fairness of Graph Neural Networks: A Graph Counterfactual Perspective

Graph neural networks have shown great ability in representation (GNNs) ...

0 Zhimeng Guo, et al. ∙

research

∙ 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 ...

8 Juanhui Li, et al. ∙

research

∙ 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...

20 Haitao Mao, et al. ∙

research

∙ 11/10/2022

Heterogeneous Randomized Response for Differential Privacy in Graph Neural Networks

Graph neural networks (GNNs) are susceptible to privacy inference attack...

0 Khang Tran, et al. ∙

research

∙ 08/30/2022

Learning Representations for Hyper-Relational Knowledge Graphs

Knowledge graphs (KGs) have gained prominence for their ability to learn...

7 Harry Shomer, et al. ∙

research

∙ 08/13/2022

Enhancing Graph Contrastive Learning with Node Similarity

Graph Neural Networks (GNNs) have achieved great success in learning gra...

7 Hongliang Chi, et al. ∙

research

∙ 06/15/2022

Feature Overcorrelation in Deep Graph Neural Networks: A New Perspective

Recent years have witnessed remarkable success achieved by graph neural ...

11 Wei Jin, et al. ∙

research

∙ 05/21/2022

Are Graph Neural Networks Really Helpful for Knowledge Graph Completion?

Knowledge graphs (KGs) facilitate a wide variety of applications due to ...

15 Juanhui Li, et al. ∙

research

∙ 04/03/2022

Graph Enhanced BERT for Query Understanding

Query understanding plays a key role in exploring users' search intents ...

0 Juanhui Li, et al. ∙

research

∙ 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...

0 Kaushik Chakraborty, et al. ∙

research

∙ 09/28/2021

Multimodality in Meta-Learning: A Comprehensive Survey

Meta-learning has gained wide popularity as a training framework that is...

0 Yao Ma, et al. ∙

research

∙ 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...

0 Yao Ma, et al. ∙

research

∙ 07/05/2021

Elastic Graph Neural Networks

While many existing graph neural networks (GNNs) have been proven to per...

0 Xiaorui Liu, et al. ∙

research

∙ 06/11/2021

Is Homophily a Necessity for Graph Neural Networks?

Graph neural networks (GNNs) have shown great prowess in learning repres...

0 Yao Ma, et al. ∙

research

∙ 06/10/2021

Automated Self-Supervised Learning for Graphs

Graph self-supervised learning has gained increasing attention due to it...

10 Wei Jin, et al. ∙

research

∙ 05/10/2021

Graph Feature Gating Networks

Graph neural networks (GNNs) have received tremendous attention due to t...

38 Wei Jin, et al. ∙

research

∙ 11/19/2020

Node Similarity Preserving Graph Convolutional Networks

Graph Neural Networks (GNNs) have achieved tremendous success in various...

26 Wei Jin, et al. ∙

research

∙ 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...

0 Yao Ma, et al. ∙

research

∙ 05/22/2020

Non-IID Graph Neural Networks

Graph classification is an important task on graph-structured data with ...

0 Yiqi Wang, et al. ∙

research

∙ 05/20/2020

Graph Structure Learning for Robust Graph Neural Networks

Graph Neural Networks (GNNs) are powerful tools in representation learni...

5 Wei Jin, et al. ∙

research

∙ 05/17/2020

Attacking Black-box Recommendations via Copying Cross-domain User Profiles

Recently, recommender systems that aim to suggest personalized lists of ...

0 Wenqi Fan, et al. ∙

research

∙ 09/17/2019

Adversarial Attacks and Defenses in Images, Graphs and Text: A Review

Deep neural networks (DNN) have achieved unprecedented success in numero...

12 Han Xu, et al. ∙

research

∙ 07/16/2019

Deep Social Collaborative Filtering

Recommender systems are crucial to alleviate the information overload pr...

0 Wenqi Fan, et al. ∙

research

∙ 07/12/2019

R-Transformer: Recurrent Neural Network Enhanced Transformer

Recurrent Neural Networks have long been the dominating choice for seque...

0 Zhiwei Wang, et al. ∙

research

∙ 06/10/2019

Attacking Graph Convolutional Networks via Rewiring

Graph Neural Networks (GNNs) have boosted the performance of many graph ...

0 Yao Ma, et al. ∙

research

∙ 05/30/2019

Deep Adversarial Social Recommendation

Recent years have witnessed rapid developments on social recommendation ...

0 Wenqi Fan, et al. ∙

research

∙ 04/30/2019

Graph Convolutional Networks with EigenPooling

Graph neural networks, which generalize deep neural network models to gr...

0 Yao Ma, et al. ∙

research

∙ 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...

12 Yao Ma, et al. ∙

research

∙ 02/19/2019

Graph Neural Networks for Social Recommendation

In recent years, Graph Neural Networks (GNNs), which can naturally integ...

0 Wenqi Fan, et al. ∙

research

∙ 10/24/2018

Dynamic Graph Neural Networks

Graphs, which describe pairwise relations between objects, are essential...

0 Yao Ma, et al. ∙

research

∙ 09/17/2018

Automata Guided Reinforcement Learning With Demonstrations

Tasks with complex temporal structures and long horizons pose a challeng...

0 Xiao Li, et al. ∙

research

∙ 08/19/2018

Linked Recurrent Neural Networks

Recurrent Neural Networks (RNNs) have been proven to be effective in mod...

0 Zhiwei Wang, et al. ∙

research

∙ 10/31/2017

Automata Guided Hierarchical Reinforcement Learning for Zero-shot Skill Composition

An obstacle that prevents the wide adoption of (deep) reinforcement lear...

0 Xiao Li, et al. ∙

research

∙ 09/27/2017

A Policy Search Method For Temporal Logic Specified Reinforcement Learning Tasks

Reward engineering is an important aspect of reinforcement learning. Whe...

0 Xiao Li, et al. ∙

research

∙ 03/10/2016

Theoretical Comparisons of Positive-Unlabeled Learning against Positive-Negative Learning

In PU learning, a binary classifier is trained from positive (P) and unl...

0 Gang Niu, et al. ∙

Yao Ma

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