Charu Aggarwal | DeepAI

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∙ 07/10/2023

Fairness and Diversity in Recommender Systems: A Survey

Recommender systems are effective tools for mitigating information overl...

0 Yuying Zhao, et al. ∙

∙ 06/02/2023

A Survey on Explainability of Graph Neural Networks

Graph neural networks (GNNs) are powerful graph-based deep-learning mode...

0 Jaykumar Kakkad, et al. ∙

∙ 04/03/2023

Counterfactual Learning on Graphs: A Survey

Graph-structured data are pervasive in the real-world such as social net...

0 Zhimeng Guo, et al. ∙

∙ 01/14/2023

A Comprehensive Survey of Graph-level Learning

Graphs have a superior ability to represent relational data, like chemic...

0 Zhenyu Yang, et al. ∙

∙ 08/03/2022

Link Prediction on Heterophilic Graphs via Disentangled Representation Learning

Link prediction is an important task that has wide applications in vario...

7 Shijie Zhou, et al. ∙

∙ 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. ∙

∙ 05/31/2022

Graph-level Neural Networks: Current Progress and Future Directions

Graph-structured data consisting of objects (i.e., nodes) and relationsh...

0 Ge Zhang, et al. ∙

∙ 05/22/2022

Sequential/Session-based Recommendations: Challenges, Approaches, Applications and Opportunities

In recent years, sequential recommender systems (SRSs) and session-based...

0 Shoujin Wang, et al. ∙

∙ 02/22/2022

Graph Lifelong Learning: A Survey

Graph learning substantially contributes to solving artificial intellige...

0 Falih Gozi Febrinanto, et al. ∙

∙ 10/22/2021

Distance-wise Prototypical Graph Neural Network in Node Imbalance Classification

Recent years have witnessed the significant success of applying graph ne...

0 Yu Wang, et al. ∙

∙ 08/07/2021

Jointly Attacking Graph Neural Network and its Explanations

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

23 Wenqi Fan, et al. ∙

∙ 07/21/2021

Bridging the Gap between Spatial and Spectral Domains: A Theoretical Framework for Graph Neural Networks

During the past decade, deep learning's performance has been widely reco...

20 Zhiqian Chen, et al. ∙

∙ 06/08/2021

NRGNN: Learning a Label Noise-Resistant Graph Neural Network on Sparsely and Noisily Labeled Graphs

Graph Neural Networks (GNNs) have achieved promising results for semi-su...

0 Enyan Dai, et al. ∙

∙ 05/10/2021

Graph Feature Gating Networks

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

38 Wei Jin, et al. ∙

∙ 02/10/2021

Information Prediction using Knowledge Graphs for Contextual Malware Threat Intelligence

Large amounts of threat intelligence information about mal-ware attacks ...

0 Nidhi Rastogi, et al. ∙

∙ 06/28/2020

Graph Convolutional Networks against Degree-Related Biases

In recent years, Graph Convolutional Networks (GCNs) show competitive pe...

0 Xianfeng Tang, et al. ∙

∙ 06/20/2020

MALOnt: An Ontology for Malware Threat Intelligence

Malware threat intelligence uncovers deep information about malware, thr...

0 Nidhi Rastogi, et al. ∙

∙ 05/22/2020

Non-IID Graph Neural Networks

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

0 Yiqi Wang, et al. ∙

∙ 11/25/2019

Efficient Global String Kernel with Random Features: Beyond Counting Substructures

Analysis of large-scale sequential data has been one of the most crucial...

0 Lingfei Wu, et al. ∙

∙ 11/25/2019

Scalable Global Alignment Graph Kernel Using Random Features: From Node Embedding to Graph Embedding

Graph kernels are widely used for measuring the similarity between graph...

0 Lingfei Wu, et al. ∙

∙ 11/22/2019

Joint Modeling of Local and Global Temporal Dynamics for Multivariate Time Series Forecasting with Missing Values

Multivariate time series (MTS) forecasting is widely used in various dom...

0 Xianfeng Tang, et al. ∙

∙ 10/22/2019

How can AI Automate End-to-End Data Science?

Data science is labor-intensive and human experts are scarce but heavily...

0 Charu Aggarwal, et al. ∙

∙ 05/25/2018

Scalable Spectral Clustering Using Random Binning Features

Spectral clustering is one of the most effective clustering approaches t...

0 Lingfei Wu, et al. ∙

∙ 05/17/2017

REMIX: Automated Exploration for Interactive Outlier Detection

Outlier detection is the identification of points in a dataset that do n...

0 Yanjie Fu, et al. ∙

∙ 03/22/2017

Joint Intermodal and Intramodal Label Transfers for Extremely Rare or Unseen Classes

In this paper, we present a label transfer model from texts to images fo...

0 Guo-Jun Qi, et al. ∙

∙ 11/24/2015

A Survey of Signed Network Mining in Social Media

Many real-world relations can be represented by signed networks with pos...

0 Jiliang Tang, et al. ∙

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