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 Liang Zhao

Liang Zhao

A Method for Inferring Polymers Based on Linear Regression and Integer Programming


Aug 24, 2021
Ryota Ido, Shengjuan Cao, Jianshen Zhu, Naveed Ahmed Azam, Kazuya Haraguchi, Liang Zhao, Hiroshi Nagamochi, Tatsuya Akutsu

Figure 1 for A Method for Inferring Polymers Based on Linear Regression and Integer Programming
Figure 2 for A Method for Inferring Polymers Based on Linear Regression and Integer Programming
Figure 3 for A Method for Inferring Polymers Based on Linear Regression and Integer Programming
Figure 4 for A Method for Inferring Polymers Based on Linear Regression and Integer Programming
* arXiv admin note: substantial text overlap with arXiv:2107.02381; text overlap with arXiv:2108.10266 
  Access Paper or Ask Questions

Molecular Design Based on Artificial Neural Networks, Integer Programming and Grid Neighbor Search


Aug 23, 2021
Naveed Ahmed Azam, Jianshen Zhu, Kazuya Haraguchi, Liang Zhao, Hiroshi Nagamochi, Tatsuya Akutsu

Figure 1 for Molecular Design Based on Artificial Neural Networks, Integer Programming and Grid Neighbor Search
Figure 2 for Molecular Design Based on Artificial Neural Networks, Integer Programming and Grid Neighbor Search
Figure 3 for Molecular Design Based on Artificial Neural Networks, Integer Programming and Grid Neighbor Search
Figure 4 for Molecular Design Based on Artificial Neural Networks, Integer Programming and Grid Neighbor Search
* arXiv admin note: substantial text overlap with arXiv:2107.02381 
  Access Paper or Ask Questions

Long-term, Short-term and Sudden Event: Trading Volume Movement Prediction with Graph-based Multi-view Modeling


Aug 23, 2021
Liang Zhao, Wei Li, Ruihan Bao, Keiko Harimoto, YunfangWu, Xu Sun

Figure 1 for Long-term, Short-term and Sudden Event: Trading Volume Movement Prediction with Graph-based Multi-view Modeling
Figure 2 for Long-term, Short-term and Sudden Event: Trading Volume Movement Prediction with Graph-based Multi-view Modeling
Figure 3 for Long-term, Short-term and Sudden Event: Trading Volume Movement Prediction with Graph-based Multi-view Modeling
Figure 4 for Long-term, Short-term and Sudden Event: Trading Volume Movement Prediction with Graph-based Multi-view Modeling
* Accepted as a main track paper by IJCAI 21 
  Access Paper or Ask Questions

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


Aug 07, 2021
Zhiqian Chen, Fanglan Chen, Lei Zhang, Taoran Ji, Kaiqun Fu, Liang Zhao, Feng Chen, Lingfei Wu, Charu Aggarwal, Chang-Tien Lu

Figure 1 for Bridging the Gap between Spatial and Spectral Domains: A Unified Framework for Graph Neural Networks
Figure 2 for Bridging the Gap between Spatial and Spectral Domains: A Unified Framework for Graph Neural Networks
Figure 3 for Bridging the Gap between Spatial and Spectral Domains: A Unified Framework for Graph Neural Networks
Figure 4 for Bridging the Gap between Spatial and Spectral Domains: A Unified Framework for Graph Neural Networks

  Access Paper or Ask Questions

Communication Efficiency in Federated Learning: Achievements and Challenges


Jul 23, 2021
Osama Shahid, Seyedamin Pouriyeh, Reza M. Parizi, Quan Z. Sheng, Gautam Srivastava, Liang Zhao

Figure 1 for Communication Efficiency in Federated Learning: Achievements and Challenges
Figure 2 for Communication Efficiency in Federated Learning: Achievements and Challenges
Figure 3 for Communication Efficiency in Federated Learning: Achievements and Challenges
Figure 4 for Communication Efficiency in Federated Learning: Achievements and Challenges

  Access Paper or Ask Questions

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


Jul 21, 2021
Zhiqian Chen, Fanglan Chen, Lei Zhang, Taoran Ji, Kaiqun Fu, Liang Zhao, Feng Chen, Lingfei Wu, Charu Aggarwal, Chang-Tien Lu

Figure 1 for Bridging the Gap between Spatial and Spectral Domains: A Theoretical Framework for Graph Neural Networks
Figure 2 for Bridging the Gap between Spatial and Spectral Domains: A Theoretical Framework for Graph Neural Networks
Figure 3 for Bridging the Gap between Spatial and Spectral Domains: A Theoretical Framework for Graph Neural Networks
Figure 4 for Bridging the Gap between Spatial and Spectral Domains: A Theoretical Framework for Graph Neural Networks

  Access Paper or Ask Questions

An Inverse QSAR Method Based on Linear Regression and Integer Programming


Jul 13, 2021
Jianshen Zhu, Naveed Ahmed Azam, Kazuya Haraguchi, Liang Zhao, Hiroshi Nagamochi, Tatsuya Akutsu

Figure 1 for An Inverse QSAR Method Based on Linear Regression and Integer Programming
Figure 2 for An Inverse QSAR Method Based on Linear Regression and Integer Programming
Figure 3 for An Inverse QSAR Method Based on Linear Regression and Integer Programming
Figure 4 for An Inverse QSAR Method Based on Linear Regression and Integer Programming

  Access Paper or Ask Questions

RefBERT: Compressing BERT by Referencing to Pre-computed Representations


Jun 11, 2021
Xinyi Wang, Haiqin Yang, Liang Zhao, Yang Mo, Jianping Shen

Figure 1 for RefBERT: Compressing BERT by Referencing to Pre-computed Representations
Figure 2 for RefBERT: Compressing BERT by Referencing to Pre-computed Representations
Figure 3 for RefBERT: Compressing BERT by Referencing to Pre-computed Representations
Figure 4 for RefBERT: Compressing BERT by Referencing to Pre-computed Representations
* 8 pages, 1 figure, 3 tables, in IJCNN'21 
  Access Paper or Ask Questions

Direct Simultaneous Multi-Image Registration


May 21, 2021
Zhehua Mao, Liang Zhao, Shoudong Huang, Yiting Fan, Alex Pui-Wai Lee

Figure 1 for Direct Simultaneous Multi-Image Registration
Figure 2 for Direct Simultaneous Multi-Image Registration
Figure 3 for Direct Simultaneous Multi-Image Registration
Figure 4 for Direct Simultaneous Multi-Image Registration
* 10 pages, 3 figures, 1 table 
  Access Paper or Ask Questions

Towards Quantized Model Parallelism for Graph-Augmented MLPs Based on Gradient-Free ADMM framework


May 20, 2021
Junxiang Wang, Hongyi Li, Zheng Chai, Yongchao Wang, Yue Cheng, Liang Zhao

Figure 1 for Towards Quantized Model Parallelism for Graph-Augmented MLPs Based on Gradient-Free ADMM framework
Figure 2 for Towards Quantized Model Parallelism for Graph-Augmented MLPs Based on Gradient-Free ADMM framework
Figure 3 for Towards Quantized Model Parallelism for Graph-Augmented MLPs Based on Gradient-Free ADMM framework
Figure 4 for Towards Quantized Model Parallelism for Graph-Augmented MLPs Based on Gradient-Free ADMM framework
* Junxiang Wang and Hongyi Li contribute equally to this work, and Yongchao Wang and Liang Zhao are corresponding authors. This work is under progress. arXiv admin note: substantial text overlap with arXiv:2009.02868 
  Access Paper or Ask Questions

Schematic Memory Persistence and Transience for Efficient and Robust Continual Learning


May 05, 2021
Yuyang Gao, Giorgio A. Ascoli, Liang Zhao

Figure 1 for Schematic Memory Persistence and Transience for Efficient and Robust Continual Learning
Figure 2 for Schematic Memory Persistence and Transience for Efficient and Robust Continual Learning
Figure 3 for Schematic Memory Persistence and Transience for Efficient and Robust Continual Learning
Figure 4 for Schematic Memory Persistence and Transience for Efficient and Robust Continual Learning
* Under review at Neural Networks - Special Issue on AI and Brain Science 
  Access Paper or Ask Questions

Interpretable Distance Metric Learning for Handwritten Chinese Character Recognition


Mar 17, 2021
Boxiang Dong, Aparna S. Varde, Danilo Stevanovic, Jiayin Wang, Liang Zhao

Figure 1 for Interpretable Distance Metric Learning for Handwritten Chinese Character Recognition
Figure 2 for Interpretable Distance Metric Learning for Handwritten Chinese Character Recognition
Figure 3 for Interpretable Distance Metric Learning for Handwritten Chinese Character Recognition
Figure 4 for Interpretable Distance Metric Learning for Handwritten Chinese Character Recognition

  Access Paper or Ask Questions

Cyber Intrusion Detection by Using Deep Neural Networks with Attack-sharing Loss


Mar 17, 2021
Boxiang Dong, Hui, Wang, Aparna S. Varde, Dawei Li, Bharath K. Samanthula, Weifeng Sun, Liang Zhao

Figure 1 for Cyber Intrusion Detection by Using Deep Neural Networks with Attack-sharing Loss
Figure 2 for Cyber Intrusion Detection by Using Deep Neural Networks with Attack-sharing Loss
Figure 3 for Cyber Intrusion Detection by Using Deep Neural Networks with Attack-sharing Loss
Figure 4 for Cyber Intrusion Detection by Using Deep Neural Networks with Attack-sharing Loss

  Access Paper or Ask Questions

Sign-regularized Multi-task Learning


Feb 22, 2021
Johnny Torres, Guangji Bai, Junxiang Wang, Liang Zhao, Carmen Vaca, Cristina Abad

Figure 1 for Sign-regularized Multi-task Learning
Figure 2 for Sign-regularized Multi-task Learning
Figure 3 for Sign-regularized Multi-task Learning
Figure 4 for Sign-regularized Multi-task Learning
* 17 pages, 4 figures, v1 
  Access Paper or Ask Questions

GP: Context-free Grammar Pre-training for Text-to-SQL Parsers


Jan 25, 2021
Liang Zhao, Hexin Cao, Yunsong Zhao

Figure 1 for GP: Context-free Grammar Pre-training for Text-to-SQL Parsers
Figure 2 for GP: Context-free Grammar Pre-training for Text-to-SQL Parsers
Figure 3 for GP: Context-free Grammar Pre-training for Text-to-SQL Parsers
Figure 4 for GP: Context-free Grammar Pre-training for Text-to-SQL Parsers

  Access Paper or Ask Questions

Online Decision Trees with Fairness


Oct 15, 2020
Wenbin Zhang, Liang Zhao

Figure 1 for Online Decision Trees with Fairness
Figure 2 for Online Decision Trees with Fairness
Figure 3 for Online Decision Trees with Fairness
Figure 4 for Online Decision Trees with Fairness
* arXiv admin note: substantial text overlap with arXiv:1907.07237 
  Access Paper or Ask Questions

Disentangled Dynamic Graph Deep Generation


Oct 14, 2020
Wenbin Zhang, Liming Zhang, Dieter Pfoser, Liang Zhao

Figure 1 for Disentangled Dynamic Graph Deep Generation
Figure 2 for Disentangled Dynamic Graph Deep Generation
Figure 3 for Disentangled Dynamic Graph Deep Generation
Figure 4 for Disentangled Dynamic Graph Deep Generation

  Access Paper or Ask Questions

FedAT: A Communication-Efficient Federated Learning Method with Asynchronous Tiers under Non-IID Data


Oct 12, 2020
Zheng Chai, Yujing Chen, Liang Zhao, Yue Cheng, Huzefa Rangwala

Figure 1 for FedAT: A Communication-Efficient Federated Learning Method with Asynchronous Tiers under Non-IID Data
Figure 2 for FedAT: A Communication-Efficient Federated Learning Method with Asynchronous Tiers under Non-IID Data
Figure 3 for FedAT: A Communication-Efficient Federated Learning Method with Asynchronous Tiers under Non-IID Data
Figure 4 for FedAT: A Communication-Efficient Federated Learning Method with Asynchronous Tiers under Non-IID Data

  Access Paper or Ask Questions

A new network-base high-level data classification methodology (Quipus) by modeling attribute-attribute interactions


Sep 28, 2020
Esteban Wilfredo Vilca Zuñiga, Liang Zhao

Figure 1 for A new network-base high-level data classification methodology (Quipus) by modeling attribute-attribute interactions
Figure 2 for A new network-base high-level data classification methodology (Quipus) by modeling attribute-attribute interactions
Figure 3 for A new network-base high-level data classification methodology (Quipus) by modeling attribute-attribute interactions
Figure 4 for A new network-base high-level data classification methodology (Quipus) by modeling attribute-attribute interactions

  Access Paper or Ask Questions

Graph-based Multi-hop Reasoning for Long Text Generation


Sep 28, 2020
Liang Zhao, Jingjing Xu, Junyang Lin, Yichang Zhang, Hongxia Yang, Xu Sun

Figure 1 for Graph-based Multi-hop Reasoning for Long Text Generation
Figure 2 for Graph-based Multi-hop Reasoning for Long Text Generation
Figure 3 for Graph-based Multi-hop Reasoning for Long Text Generation
Figure 4 for Graph-based Multi-hop Reasoning for Long Text Generation

  Access Paper or Ask Questions

Factorized Deep Generative Models for Trajectory Generation with Spatiotemporal-Validity Constraints


Sep 20, 2020
Liming Zhang, Liang Zhao, Dieter Pfoser

Figure 1 for Factorized Deep Generative Models for Trajectory Generation with Spatiotemporal-Validity Constraints
Figure 2 for Factorized Deep Generative Models for Trajectory Generation with Spatiotemporal-Validity Constraints
Figure 3 for Factorized Deep Generative Models for Trajectory Generation with Spatiotemporal-Validity Constraints
Figure 4 for Factorized Deep Generative Models for Trajectory Generation with Spatiotemporal-Validity Constraints

  Access Paper or Ask Questions

A Network-Based High-Level Data Classification Algorithm Using Betweenness Centrality


Sep 16, 2020
Esteban Vilca, Liang Zhao

Figure 1 for A Network-Based High-Level Data Classification Algorithm Using Betweenness Centrality
Figure 2 for A Network-Based High-Level Data Classification Algorithm Using Betweenness Centrality
Figure 3 for A Network-Based High-Level Data Classification Algorithm Using Betweenness Centrality
Figure 4 for A Network-Based High-Level Data Classification Algorithm Using Betweenness Centrality

  Access Paper or Ask Questions

Tunable Subnetwork Splitting for Model-parallelism of Neural Network Training


Sep 16, 2020
Junxiang Wang, Zheng Chai, Yue Cheng, Liang Zhao

Figure 1 for Tunable Subnetwork Splitting for Model-parallelism of Neural Network Training
Figure 2 for Tunable Subnetwork Splitting for Model-parallelism of Neural Network Training
Figure 3 for Tunable Subnetwork Splitting for Model-parallelism of Neural Network Training
* ICML 2020 Workshop on "Beyond first-order methods in ML systems" 
  Access Paper or Ask Questions

Event Prediction in the Big Data Era: A Systematic Survey


Aug 04, 2020
Liang Zhao

Figure 1 for Event Prediction in the Big Data Era: A Systematic Survey
Figure 2 for Event Prediction in the Big Data Era: A Systematic Survey
Figure 3 for Event Prediction in the Big Data Era: A Systematic Survey
Figure 4 for Event Prediction in the Big Data Era: A Systematic Survey

  Access Paper or Ask Questions

Event Prediction in Big Data Era: A Systematic Survey


Jul 21, 2020
Liang Zhao

Figure 1 for Event Prediction in Big Data Era: A Systematic Survey
Figure 2 for Event Prediction in Big Data Era: A Systematic Survey
Figure 3 for Event Prediction in Big Data Era: A Systematic Survey
Figure 4 for Event Prediction in Big Data Era: A Systematic Survey

  Access Paper or Ask Questions

A Systematic Survey on Deep Generative Models for Graph Generation


Jul 18, 2020
Xiaojie Guo, Liang Zhao

Figure 1 for A Systematic Survey on Deep Generative Models for Graph Generation
Figure 2 for A Systematic Survey on Deep Generative Models for Graph Generation
Figure 3 for A Systematic Survey on Deep Generative Models for Graph Generation
Figure 4 for A Systematic Survey on Deep Generative Models for Graph Generation

  Access Paper or Ask Questions