Get our free extension to see links to code for papers anywhere online!

Chrome logo Add to Chrome

Firefox logo Add to Firefox
Picture for Philip S. Yu

Philip S. Yu

HTCInfoMax: A Global Model for Hierarchical Text Classification via Information Maximization


Apr 12, 2021
Zhongfen Deng, Hao Peng, Dongxiao He, Jianxin Li, Philip S. Yu

* Accepted by NAACL-HLT 2021 
  Access Paper or Ask Questions

Hyperbolic Variational Graph Neural Network for Modeling Dynamic Graphs


Apr 06, 2021
Li Sun, Zhongbao Zhang, Jiawei Zhang, Feiyang Wang, Hao Peng, Sen Su, Philip S. Yu

Figure 1 for Hyperbolic Variational Graph Neural Network for Modeling Dynamic Graphs
Figure 2 for Hyperbolic Variational Graph Neural Network for Modeling Dynamic Graphs
Figure 3 for Hyperbolic Variational Graph Neural Network for Modeling Dynamic Graphs
Figure 4 for Hyperbolic Variational Graph Neural Network for Modeling Dynamic Graphs
* 9 pages, Accepted as a regular paper in AAAI Conference on Artificial Intelligence 2021 
  Access Paper or Ask Questions

Streaming Social Event Detection and Evolution Discovery in Heterogeneous Information Networks


Apr 02, 2021
Hao Peng, Jianxin Li, Yangqiu Song, Renyu Yang, Rajiv Ranjan, Philip S. Yu, Lifang He

Figure 1 for Streaming Social Event Detection and Evolution Discovery in Heterogeneous Information Networks
Figure 2 for Streaming Social Event Detection and Evolution Discovery in Heterogeneous Information Networks
Figure 3 for Streaming Social Event Detection and Evolution Discovery in Heterogeneous Information Networks
Figure 4 for Streaming Social Event Detection and Evolution Discovery in Heterogeneous Information Networks
* Accepted by TKDD 2021. arXiv admin note: text overlap with arXiv:1906.04580 
  Access Paper or Ask Questions

I-ODA, Real-World Multi-modal Longitudinal Data for OphthalmicApplications


Mar 30, 2021
Nooshin Mojab, Vahid Noroozi, Abdullah Aleem, Manoj P. Nallabothula, Joseph Baker, Dimitri T. Azar, Mark Rosenblatt, RV Paul Chan, Darvin Yi, Philip S. Yu, Joelle A. Hallak

Figure 1 for I-ODA, Real-World Multi-modal Longitudinal Data for OphthalmicApplications
Figure 2 for I-ODA, Real-World Multi-modal Longitudinal Data for OphthalmicApplications
Figure 3 for I-ODA, Real-World Multi-modal Longitudinal Data for OphthalmicApplications
Figure 4 for I-ODA, Real-World Multi-modal Longitudinal Data for OphthalmicApplications

  Access Paper or Ask Questions

An Introduction to Robust Graph Convolutional Networks


Mar 27, 2021
Mehrnaz Najafi, Philip S. Yu

Figure 1 for An Introduction to Robust Graph Convolutional Networks
Figure 2 for An Introduction to Robust Graph Convolutional Networks
Figure 3 for An Introduction to Robust Graph Convolutional Networks
Figure 4 for An Introduction to Robust Graph Convolutional Networks

  Access Paper or Ask Questions

PredRNN: A Recurrent Neural Network for Spatiotemporal Predictive Learning


Mar 18, 2021
Yunbo Wang, Haixu Wu, Jianjin Zhang, Zhifeng Gao, Jianmin Wang, Philip S. Yu, Mingsheng Long

Figure 1 for PredRNN: A Recurrent Neural Network for Spatiotemporal Predictive Learning
Figure 2 for PredRNN: A Recurrent Neural Network for Spatiotemporal Predictive Learning
Figure 3 for PredRNN: A Recurrent Neural Network for Spatiotemporal Predictive Learning
Figure 4 for PredRNN: A Recurrent Neural Network for Spatiotemporal Predictive Learning

  Access Paper or Ask Questions

BCFNet: A Balanced Collaborative Filtering Network with Attention Mechanism


Mar 10, 2021
Chang-Dong Wang, Zi-Yuan Hu, Jin Huang, Zhi-Hong Deng, Ling Huang, Jian-Huang Lai, Philip S. Yu

Figure 1 for BCFNet: A Balanced Collaborative Filtering Network with Attention Mechanism
Figure 2 for BCFNet: A Balanced Collaborative Filtering Network with Attention Mechanism
Figure 3 for BCFNet: A Balanced Collaborative Filtering Network with Attention Mechanism
Figure 4 for BCFNet: A Balanced Collaborative Filtering Network with Attention Mechanism

  Access Paper or Ask Questions

Graph Self-Supervised Learning: A Survey


Feb 27, 2021
Yixin Liu, Shirui Pan, Ming Jin, Chuan Zhou, Feng Xia, Philip S. Yu

Figure 1 for Graph Self-Supervised Learning: A Survey
Figure 2 for Graph Self-Supervised Learning: A Survey
Figure 3 for Graph Self-Supervised Learning: A Survey
* 8 pages, 2 figures, has been submitted to IJCAI 2021 Survey Track 
  Access Paper or Ask Questions

Knowledge-Preserving Incremental Social Event Detection via Heterogeneous GNNs


Feb 13, 2021
Yuwei Cao, Hao Peng, Jia Wu, Yingtong Dou, Jianxin Li, Philip S. Yu

Figure 1 for Knowledge-Preserving Incremental Social Event Detection via Heterogeneous GNNs
Figure 2 for Knowledge-Preserving Incremental Social Event Detection via Heterogeneous GNNs
Figure 3 for Knowledge-Preserving Incremental Social Event Detection via Heterogeneous GNNs
Figure 4 for Knowledge-Preserving Incremental Social Event Detection via Heterogeneous GNNs
* This work has been accepted to The Web Conference 2021 
  Access Paper or Ask Questions

Enriching Non-Autoregressive Transformer with Syntactic and SemanticStructures for Neural Machine Translation


Jan 22, 2021
Ye Liu, Yao Wan, Jian-Guo Zhang, Wenting Zhao, Philip S. Yu

Figure 1 for Enriching Non-Autoregressive Transformer with Syntactic and SemanticStructures for Neural Machine Translation
Figure 2 for Enriching Non-Autoregressive Transformer with Syntactic and SemanticStructures for Neural Machine Translation
Figure 3 for Enriching Non-Autoregressive Transformer with Syntactic and SemanticStructures for Neural Machine Translation
Figure 4 for Enriching Non-Autoregressive Transformer with Syntactic and SemanticStructures for Neural Machine Translation
* 10 pages, Appear in EACL 2021 
  Access Paper or Ask Questions

Dynamic Bicycle Dispatching of Dockless Public Bicycle-sharing Systems using Multi-objective Reinforcement Learning


Jan 19, 2021
Jianguo Chen, Kenli Li, Keqin Li, Philip S. Yu, Zeng Zeng

Figure 1 for Dynamic Bicycle Dispatching of Dockless Public Bicycle-sharing Systems using Multi-objective Reinforcement Learning
Figure 2 for Dynamic Bicycle Dispatching of Dockless Public Bicycle-sharing Systems using Multi-objective Reinforcement Learning
Figure 3 for Dynamic Bicycle Dispatching of Dockless Public Bicycle-sharing Systems using Multi-objective Reinforcement Learning
Figure 4 for Dynamic Bicycle Dispatching of Dockless Public Bicycle-sharing Systems using Multi-objective Reinforcement Learning

  Access Paper or Ask Questions

Dynamic Planning of Bicycle Stations in Dockless Public Bicycle-sharing System Using Gated Graph Neural Network


Jan 19, 2021
Jianguo Chen, Kenli Li, Keqin Li, Philip S. Yu, Zeng Zeng

Figure 1 for Dynamic Planning of Bicycle Stations in Dockless Public Bicycle-sharing System Using Gated Graph Neural Network
Figure 2 for Dynamic Planning of Bicycle Stations in Dockless Public Bicycle-sharing System Using Gated Graph Neural Network
Figure 3 for Dynamic Planning of Bicycle Stations in Dockless Public Bicycle-sharing System Using Gated Graph Neural Network
Figure 4 for Dynamic Planning of Bicycle Stations in Dockless Public Bicycle-sharing System Using Gated Graph Neural Network

  Access Paper or Ask Questions

Heterogeneous Similarity Graph Neural Network on Electronic Health Records


Jan 17, 2021
Zheng Liu, Xiaohan Li, Hao Peng, Lifang He, Philip S. Yu

Figure 1 for Heterogeneous Similarity Graph Neural Network on Electronic Health Records
Figure 2 for Heterogeneous Similarity Graph Neural Network on Electronic Health Records
Figure 3 for Heterogeneous Similarity Graph Neural Network on Electronic Health Records
Figure 4 for Heterogeneous Similarity Graph Neural Network on Electronic Health Records

  Access Paper or Ask Questions

Dynamic Graph Collaborative Filtering


Jan 08, 2021
Xiaohan Li, Mengqi Zhang, Shu Wu, Zheng Liu, Liang Wang, Philip S. Yu

Figure 1 for Dynamic Graph Collaborative Filtering
Figure 2 for Dynamic Graph Collaborative Filtering
Figure 3 for Dynamic Graph Collaborative Filtering
Figure 4 for Dynamic Graph Collaborative Filtering
* ICDM 2020 Regular paper 
  Access Paper or Ask Questions

A Survey of Community Detection Approaches: From Statistical Modeling to Deep Learning


Jan 03, 2021
Di Jin, Zhizhi Yu, Pengfei Jiao, Shirui Pan, Philip S. Yu, Weixiong Zhang

Figure 1 for A Survey of Community Detection Approaches: From Statistical Modeling to Deep Learning
Figure 2 for A Survey of Community Detection Approaches: From Statistical Modeling to Deep Learning
Figure 3 for A Survey of Community Detection Approaches: From Statistical Modeling to Deep Learning
Figure 4 for A Survey of Community Detection Approaches: From Statistical Modeling to Deep Learning

  Access Paper or Ask Questions

Privacy and Robustness in Federated Learning: Attacks and Defenses


Dec 07, 2020
Lingjuan Lyu, Han Yu, Xingjun Ma, Lichao Sun, Jun Zhao, Qiang Yang, Philip S. Yu

Figure 1 for Privacy and Robustness in Federated Learning: Attacks and Defenses
Figure 2 for Privacy and Robustness in Federated Learning: Attacks and Defenses
Figure 3 for Privacy and Robustness in Federated Learning: Attacks and Defenses
Figure 4 for Privacy and Robustness in Federated Learning: Attacks and Defenses
* arXiv admin note: text overlap with arXiv:2003.02133; text overlap with arXiv:1911.11815 by other authors 
  Access Paper or Ask Questions

A Survey on Heterogeneous Graph Embedding: Methods, Techniques, Applications and Sources


Nov 30, 2020
Xiao Wang, Deyu Bo, Chuan Shi, Shaohua Fan, Yanfang Ye, Philip S. Yu

Figure 1 for A Survey on Heterogeneous Graph Embedding: Methods, Techniques, Applications and Sources
Figure 2 for A Survey on Heterogeneous Graph Embedding: Methods, Techniques, Applications and Sources
Figure 3 for A Survey on Heterogeneous Graph Embedding: Methods, Techniques, Applications and Sources
Figure 4 for A Survey on Heterogeneous Graph Embedding: Methods, Techniques, Applications and Sources
* Under review 
  Access Paper or Ask Questions

Hierarchical Bi-Directional Self-Attention Networks for Paper Review Rating Recommendation


Nov 02, 2020
Zhongfen Deng, Hao Peng, Congying Xia, Jianxin Li, Lifang He, Philip S. Yu

Figure 1 for Hierarchical Bi-Directional Self-Attention Networks for Paper Review Rating Recommendation
Figure 2 for Hierarchical Bi-Directional Self-Attention Networks for Paper Review Rating Recommendation
Figure 3 for Hierarchical Bi-Directional Self-Attention Networks for Paper Review Rating Recommendation
Figure 4 for Hierarchical Bi-Directional Self-Attention Networks for Paper Review Rating Recommendation
* Accepted by COLING 2020 
  Access Paper or Ask Questions

Understanding Pre-trained BERT for Aspect-based Sentiment Analysis


Oct 31, 2020
Hu Xu, Lei Shu, Philip S. Yu, Bing Liu

Figure 1 for Understanding Pre-trained BERT for Aspect-based Sentiment Analysis
Figure 2 for Understanding Pre-trained BERT for Aspect-based Sentiment Analysis
Figure 3 for Understanding Pre-trained BERT for Aspect-based Sentiment Analysis
Figure 4 for Understanding Pre-trained BERT for Aspect-based Sentiment Analysis
* COLING 2020 
  Access Paper or Ask Questions

Discriminative Nearest Neighbor Few-Shot Intent Detection by Transferring Natural Language Inference


Oct 25, 2020
Jian-Guo Zhang, Kazuma Hashimoto, Wenhao Liu, Chien-Sheng Wu, Yao Wan, Philip S. Yu, Richard Socher, Caiming Xiong

Figure 1 for Discriminative Nearest Neighbor Few-Shot Intent Detection by Transferring Natural Language Inference
Figure 2 for Discriminative Nearest Neighbor Few-Shot Intent Detection by Transferring Natural Language Inference
Figure 3 for Discriminative Nearest Neighbor Few-Shot Intent Detection by Transferring Natural Language Inference
Figure 4 for Discriminative Nearest Neighbor Few-Shot Intent Detection by Transferring Natural Language Inference
* 19 pages, accepted by EMNLP 2020 main conference as a long paper. Code will be available at https://github.com/salesforce/DNNC-few-shot-intent 
  Access Paper or Ask Questions

Basket Recommendation with Multi-Intent Translation Graph Neural Network


Oct 22, 2020
Zhiwei Liu, Xiaohan Li, Ziwei Fan, Stephen Guo, Kannan Achan, Philip S. Yu

Figure 1 for Basket Recommendation with Multi-Intent Translation Graph Neural Network
Figure 2 for Basket Recommendation with Multi-Intent Translation Graph Neural Network
Figure 3 for Basket Recommendation with Multi-Intent Translation Graph Neural Network
Figure 4 for Basket Recommendation with Multi-Intent Translation Graph Neural Network
* 978-1-7281-6251-5/20/\$31.00~\copyright2020 IEEE 
 * Accepted to IEEE Bigdata 2020. Code is available online at https://github.com/JimLiu96/MITGNN 
  Access Paper or Ask Questions

Cross-Supervised Joint-Event-Extraction with Heterogeneous Information Networks


Oct 14, 2020
Yue Wang, Zhuo Xu, Lu Bai, Yao Wan, Lixin Cui, Qian Zhao, Edwin R. Hancock, Philip S. Yu

Figure 1 for Cross-Supervised Joint-Event-Extraction with Heterogeneous Information Networks
Figure 2 for Cross-Supervised Joint-Event-Extraction with Heterogeneous Information Networks
Figure 3 for Cross-Supervised Joint-Event-Extraction with Heterogeneous Information Networks
Figure 4 for Cross-Supervised Joint-Event-Extraction with Heterogeneous Information Networks
* Accepted by ICPR 2020 
  Access Paper or Ask Questions

Dynamic Semantic Matching and Aggregation Network for Few-shot Intent Detection


Oct 11, 2020
Hoang Nguyen, Chenwei Zhang, Congying Xia, Philip S. Yu

Figure 1 for Dynamic Semantic Matching and Aggregation Network for Few-shot Intent Detection
Figure 2 for Dynamic Semantic Matching and Aggregation Network for Few-shot Intent Detection
Figure 3 for Dynamic Semantic Matching and Aggregation Network for Few-shot Intent Detection
Figure 4 for Dynamic Semantic Matching and Aggregation Network for Few-shot Intent Detection
* 10 pages, 3 figures. To appear in Findings of EMNLP 2020 
  Access Paper or Ask Questions

Mixup-Transfomer: Dynamic Data Augmentation for NLP Tasks


Oct 05, 2020
Lichao Sun, Congying Xia, Wenpeng Yin, Tingting Liang, Philip S. Yu, Lifang He

Figure 1 for Mixup-Transfomer: Dynamic Data Augmentation for NLP Tasks
Figure 2 for Mixup-Transfomer: Dynamic Data Augmentation for NLP Tasks
Figure 3 for Mixup-Transfomer: Dynamic Data Augmentation for NLP Tasks
Figure 4 for Mixup-Transfomer: Dynamic Data Augmentation for NLP Tasks
* Accepted by COLING 2020 
  Access Paper or Ask Questions

Addressing Class Imbalance in Scene Graph Parsing by Learning to Contrast and Score


Oct 05, 2020
He Huang, Shunta Saito, Yuta Kikuchi, Eiichi Matsumoto, Wei Tang, Philip S. Yu

Figure 1 for Addressing Class Imbalance in Scene Graph Parsing by Learning to Contrast and Score
Figure 2 for Addressing Class Imbalance in Scene Graph Parsing by Learning to Contrast and Score
Figure 3 for Addressing Class Imbalance in Scene Graph Parsing by Learning to Contrast and Score
Figure 4 for Addressing Class Imbalance in Scene Graph Parsing by Learning to Contrast and Score
* ACCV 2020 
  Access Paper or Ask Questions

KG-BART: Knowledge Graph-Augmented BART for Generative Commonsense Reasoning


Sep 26, 2020
Ye Liu, Yao Wan, Lifang He, Hao Peng, Philip S. Yu

Figure 1 for KG-BART: Knowledge Graph-Augmented BART for Generative Commonsense Reasoning
Figure 2 for KG-BART: Knowledge Graph-Augmented BART for Generative Commonsense Reasoning
Figure 3 for KG-BART: Knowledge Graph-Augmented BART for Generative Commonsense Reasoning
Figure 4 for KG-BART: Knowledge Graph-Augmented BART for Generative Commonsense Reasoning
* 9 pages, 7 figures 
  Access Paper or Ask Questions

Fairness in Semi-supervised Learning: Unlabeled Data Help to Reduce Discrimination


Sep 25, 2020
Tao Zhang, Tianqing Zhu, Jing Li, Mengde Han, Wanlei Zhou, Philip S. Yu

Figure 1 for Fairness in Semi-supervised Learning: Unlabeled Data Help to Reduce Discrimination
Figure 2 for Fairness in Semi-supervised Learning: Unlabeled Data Help to Reduce Discrimination
Figure 3 for Fairness in Semi-supervised Learning: Unlabeled Data Help to Reduce Discrimination
Figure 4 for Fairness in Semi-supervised Learning: Unlabeled Data Help to Reduce Discrimination
* This paper has been published in IEEE Transactions on Knowledge and Data Engineering 
  Access Paper or Ask Questions