Lu Bai

According to our database, Lu Bai authored at least 121 papers between 2011 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Multimodal graph learning with framelet-based stochastic configuration networks for emotion recognition in conversation.

Jiandong Shi, Ming Li, Yuting Chen, Lixin Cui, Lu Bai

Inf. Sci., 2025

2024

HAQJSK: Hierarchical-Aligned Quantum Jensen-Shannon Kernels for Graph Classification.

Lu Bai, Lixin Cui, Yue Wang, Ming Li, Jing Li, Philip S. Yu, Edwin R. Hancock

IEEE Trans. Knowl. Data Eng., November, 2024

Multimodal graph learning based on 3D Haar semi-tight framelet for student engagement prediction.

Ming Li, Xiaosheng Zhuang, Lu Bai, Weiping Ding

Inf. Fusion, May, 2024

Learning Aligned Vertex Convolutional Networks for Graph Classification.

Lixin Cui, Lu Bai, Xiao Bai, Yue Wang, Edwin R. Hancock

IEEE Trans. Neural Networks Learn. Syst., April, 2024

Collaborative Knowledge Graph Fusion by Exploiting the Open Corpus.

Yue Wang, Yao Wan, Lu Bai, Lixin Cui, Zhuo Xu, Ming Li, Philip S. Yu, Edwin R. Hancock

IEEE Trans. Knowl. Data Eng., February, 2024

QBER: Quantum-based Entropic Representations for un-attributed graphs.

Lixin Cui, Ming Li, Lu Bai, Yue Wang, Jing Li, Yanchao Wang, Zhao Li, Yunwen Chen, Edwin R. Hancock

Pattern Recognit., January, 2024

Metalantis: A Comprehensive Underwater Image Enhancement Framework.

Hao Wang, Weibo Zhang, Lu Bai, Peng Ren

IEEE Trans. Geosci. Remote. Sens., 2024

Knowledge Probing for Graph Representation Learning.

Mingyu Zhao, Xingyu Huang, Ziyu Lyu, Yanlin Wang, Lixin Cui, Lu Bai

CoRR, 2024

HC-GAE: The Hierarchical Cluster-based Graph Auto-Encoder for Graph Representation Learning.

Zhuo Xu, Lu Bai, Lixin Cui, Ming Li, Yue Wang, Edwin R. Hancock

CoRR, 2024

ENADPool: The Edge-Node Attention-based Differentiable Pooling for Graph Neural Networks.

Zhehan Zhao, Lu Bai, Lixin Cui, Ming Li, Yue Wang, Lixiang Xu, Edwin R. Hancock

CoRR, 2024

Dual-modal Prior Semantic Guided Infrared and Visible Image Fusion for Intelligent Transportation System.

Jing Li, Lu Bai, Bin Yang, Chang Li, Lingfei Ma, Lixin Cui, Edwin R. Hancock

CoRR, 2024

SSHPool: The Separated Subgraph-based Hierarchical Pooling.

Zhuo Xu, Lixin Cui, Yue Wang, Hangyuan Du, Lu Bai, Edwin R. Hancock

CoRR, 2024

AKBR: Learning Adaptive Kernel-based Representations for Graph Classification.

Feifei Qian, Lixin Cui, Yue Wang, Hangyuan Du, Lu Bai, Edwin R. Hancock

CoRR, 2024

Population Aging and High-Quality Economic Development: Based on Feature Selection and Empirical Analysis of Provincial Panel Data.

Luomeng Zhang, Lixin Cui, Lu Bai

Proceedings of the E-Business. New Challenges and Opportunities for Digital-Enabled Intelligent Future, 2024

QBMK: Quantum-based Matching Kernels for Un-attributed Graphs.

Lu Bai, Lixin Cui, Ming Li, Yue Wang, Edwin R. Hancock

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

BLoG: Bootstrapped graph representation learning with local and global regularization for recommendation.

Ming Li, Lin Zhang, Lixin Cui, Lu Bai, Zhao Li, Xindong Wu

Pattern Recognit., December, 2023

Multiple Pedestrian Tracking With Graph Attention Map on Urban Road Scene.

Zhihui Wang, Zhiyuan Li, Jiaxu Leng, Ming Li, Lu Bai

IEEE Trans. Intell. Transp. Syst., August, 2023

Graph Motif Entropy for Understanding Time-Evolving Networks.

Zhihong Zhang, Dongdong Chen, Lu Bai, Jianjia Wang, Edwin R. Hancock

IEEE Trans. Neural Networks Learn. Syst., April, 2023

Entropic Dynamic Time Warping Kernels for Co-Evolving Financial Time Series Analysis.

Lu Bai, Lixin Cui, Zhihong Zhang, Lixiang Xu, Yue Wang, Edwin R. Hancock

IEEE Trans. Neural Networks Learn. Syst., April, 2023

Learning Graph Convolutional Networks Based on Quantum Vertex Information Propagation.

Lu Bai, Yuhang Jiao, Lixin Cui, Luca Rossi, Yue Wang, Philip S. Yu, Edwin R. Hancock

IEEE Trans. Knowl. Data Eng., 2023

TFIV: Multigrained Token Fusion for Infrared and Visible Image via Transformer.

Jing Li, Bin Yang, Lu Bai, Hao Dou, Chang Li, Lingfei Ma

IEEE Trans. Instrum. Meas., 2023

Graph Representation Learning for Infrared and Visible Image Fusion.

Jing Li, Lu Bai, Bin Yang, Chang Li, Lingfei Ma, Edwin R. Hancock

CoRR, 2023

AERK: Aligned Entropic Reproducing Kernels through Continuous-time Quantum Walks.

Lixin Cui, Ming Li, Yue Wang, Lu Bai, Edwin R. Hancock

CoRR, 2023

C2N-ABDP: Cluster-to-Node Attention-Based Differentiable Pooling.

Rongji Ye, Lixin Cui, Luca Rossi, Yue Wang, Zhuo Xu, Lu Bai, Edwin R. Hancock

Proceedings of the Graph-Based Representations in Pattern Recognition, 2023

2022

Learning Backtrackless Aligned-Spatial Graph Convolutional Networks for Graph Classification.

Lu Bai, Lixin Cui, Yuhang Jiao, Luca Rossi, Edwin R. Hancock

IEEE Trans. Pattern Anal. Mach. Intell., 2022

QESK: Quantum-based Entropic Subtree Kernels for Graph Classification.

Lu Bai, Lixin Cui, Edwin R. Hancock

CoRR, 2022

HAQJSK: Hierarchical-Aligned Quantum Jensen-Shannon Kernels for Graph Classification.

Lu Bai, Lixin Cui, Yue Wang, Ming Li, Edwin R. Hancock

CoRR, 2022

Writing Style Aware Document-level Event Extraction.

Zhuo Xu, Yue Wang, Lu Bai, Lixin Cui

CoRR, 2022

ABDPool: Attention-based Differentiable Pooling.

Yue Liu, Lixin Cui, Yue Wang, Lu Bai

Proceedings of the 26th International Conference on Pattern Recognition, 2022

A Hierarchical Transitive-Aligned Graph Kernel for Un-attributed Graphs.

Lu Bai, Lixin Cui, Edwin R. Hancock

Proceedings of the International Conference on Machine Learning, 2022

Learning Graph Convolutional Networks based on Quantum Vertex Information Propagation (Extended Abstract).

Lu Bai, Yuhang Jiao, Lixin Cui, Luca Rossi, Yue Wang, Philip S. Yu, Edwin R. Hancock

Proceedings of the 38th IEEE International Conference on Data Engineering, 2022

2021

Deep Rényi entropy graph kernel.

Lixiang Xu, Lu Bai, Xiaoyi Jiang, Ming Tan, Daoqiang Zhang, Bin Luo

Pattern Recognit., 2021

Internet financing credit risk evaluation using multiple structural interacting elastic net feature selection.

Lixin Cui, Lu Bai, Yanchao Wang, Xin Jin, Edwin R. Hancock

Pattern Recognit., 2021

Fused lasso for feature selection using structural information.

Lixin Cui, Lu Bai, Yue Wang, Philip S. Yu, Edwin R. Hancock

Pattern Recognit., 2021

Multiple graph kernel learning based on GMDH-type neural network.

Lixiang Xu, Lu Bai, Jin Xiao, Qi Liu, Enhong Chen, Xiaofeng Wang, Yuanyan Tang

Inf. Fusion, 2021

ABAE: Utilize Attention to Boost Graph Auto-Encoder.

Tianyu Liu, Yifan Li, Yujie Sun, Lixin Cui, Lu Bai

Proceedings of the PRICAI 2021: Trends in Artificial Intelligence, 2021

2020

Generative temporal link prediction via self-tokenized sequence modeling.

Yue Wang, Chenwei Zhang, Shen Wang, Philip S. Yu, Lu Bai, Lixin Cui, Guandong Xu

World Wide Web, 2020

A Quantum-Inspired Similarity Measure for the Analysis of Complete Weighted Graphs.

Lu Bai, Luca Rossi, Lixin Cui, Jian Cheng, Edwin R. Hancock

IEEE Trans. Cybern., 2020

Local-global nested graph kernels using nested complexity traces.

Lu Bai, Lixin Cui, Luca Rossi, Lixiang Xu, Xiao Bai, Edwin R. Hancock

Pattern Recognit. Lett., 2020

Spectral bounding: Strictly satisfying the 1-Lipschitz property for generative adversarial networks.

Zhihong Zhang, Yangbin Zeng, Lu Bai, Yiqun Hu, Meihong Wu, Shuai Wang, Edwin R. Hancock

Pattern Recognit., 2020

Probabilistic SVM classifier ensemble selection based on GMDH-type neural network.

Lixiang Xu, Xiaofeng Wang, Lu Bai, Jin Xiao, Qi Liu, Enhong Chen, Xiaoyi Jiang, Bin Luo

Pattern Recognit., 2020

Graph Transformer: Learning Better Representations for Graph Neural Networks.

Boyuan Wang, Lixin Cui, Lu Bai, Edwin R. Hancock

Proceedings of the Structural, Syntactic, and Statistical Pattern Recognition, 2020

LGL-GNN: Learning Global and Local Information for Graph Neural Networks.

Huan Li, Boyuan Wang, Lixin Cui, Lu Bai, Edwin R. Hancock

Proceedings of the Structural, Syntactic, and Statistical Pattern Recognition, 2020

Alzheimer's Brain Network Analysis Using Sparse Learning Feature Selection.

Lixin Cui, Lichi Zhang, Lu Bai, Yue Wang, Edwin R. Hancock

Proceedings of the Structural, Syntactic, and Statistical Pattern Recognition, 2020

A Quantum-inspired Entropic Kernel for Multiple Financial Time Series Analysis.

Lu Bai, Lixin Cui, Yue Wang, Yuhang Jiao, Edwin R. Hancock

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

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

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

Proceedings of the 25th International Conference on Pattern Recognition, 2020

2019

Depth-based subgraph convolutional auto-encoder for network representation learning.

Zhihong Zhang, Dongdong Chen, Zeli Wang, Heng Li, Lu Bai, Edwin R. Hancock

Pattern Recognit., 2019

Quantum-based subgraph convolutional neural networks.

Zhihong Zhang, Dongdong Chen, Jianjia Wang, Lu Bai, Edwin R. Hancock

Pattern Recognit., 2019

Identifying the most informative features using a structurally interacting elastic net.

Lixin Cui, Lu Bai, Zhihong Zhang, Yue Wang, Edwin R. Hancock

Neurocomputing, 2019

Deep depth-based representations of graphs through deep learning networks.

Lu Bai, Lixin Cui, Xiao Bai, Edwin R. Hancock

Neurocomputing, 2019

Fused Lasso for Feature Selection using Structural Information.

Lixin Cui, Lu Bai, Edwin R. Hancock

CoRR, 2019

Learning Vertex Convolutional Networks for Graph Classification.

Lu Bai, Lixin Cui, Shu Wu, Yuhang Jiao, Edwin R. Hancock

CoRR, 2019

Learning Aligned-Spatial Graph Convolutional Networks for Graph Classification.

Lu Bai, Yuhang Jiao, Lixin Cui, Edwin R. Hancock

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2019

Loan Recommendation in P2P Lending Investment Networks: A Hybrid Graph Convolution Approach.

Yibo Chai, Yahu Cong, Lu Bai, Lixin Cui

Proceedings of the 2019 IEEE International Conference on Industrial Engineering and Engineering Management, 2019

Competitive Multi-agent Deep Reinforcement Learning with Counterfactual Thinking.

Yue Wang, Yao Wan, Chenwei Zhang, Lu Bai, Lixin Cui, Philip S. Yu

Proceedings of the 2019 IEEE International Conference on Data Mining, 2019

An Attributed Graph Embedding Method Using the Tree-Index Algorithm.

Yuhang Jiao, Yueting Yang, Lixin Cui, Lu Bai

Proceedings of the Graph-Based Representations in Pattern Recognition, 2019

2018

Nonlocal Similarity Based Nonnegative Tucker Decomposition for Hyperspectral Image Denoising.

Xiao Bai, Fan Xu, Lei Zhou, Yan Xing, Lu Bai, Jun Zhou

IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2018

A hybrid reproducing graph kernel based on information entropy.

Lixiang Xu, Xiaoyi Jiang, Lu Bai, Jin Xiao, Bin Luo

Pattern Recognit., 2018

Adaptive hash retrieval with kernel based similarity.

Xiao Bai, Cheng Yan, Haichuan Yang, Lu Bai, Jun Zhou, Edwin Robert Hancock

Pattern Recognit., 2018

基于出行模式子图的城市功能区域发现方法 (City Functional Region Discovery Algorithm Based on Travel Pattern Subgraph).

Fei Xiao, Yue Wang, Yinan Mei, Lu Bai, Lixin Cui

计算机科学, 2018

A Quantum Spatial Graph Convolutional Neural Network using Quantum Passing Information.

Lu Bai, Yuhang Jiao, Luca Rossi, Lixin Cui, Jian Cheng, Edwin R. Hancock

CoRR, 2018

Single Image Super Resolution via Neighbor Reconstruction.

Zhihong Zhang, Zhuobin Xu, Zhiling Ye, Yiqun Hu, Lixin Cui, Lu Bai

Proceedings of the Structural, Syntactic, and Statistical Pattern Recognition, 2018

Directed Network Analysis Using Transfer Entropy Component Analysis.

Meihong Wu, Yangbin Zeng, Zhihong Zhang, Haiyun Hong, Zhuobin Xu, Lixin Cui, Lu Bai, Edwin R. Hancock

Proceedings of the Structural, Syntactic, and Statistical Pattern Recognition, 2018

Analyzing Time Series from Chinese Financial Market Using a Linear-Time Graph Kernel.

Yuhang Jiao, Lixin Cui, Lu Bai, Yue Wang

Proceedings of the Structural, Syntactic, and Statistical Pattern Recognition, 2018

A Mixed Entropy Local-Global Reproducing Kernel for Attributed Graphs.

Lixin Cui, Lu Bai, Luca Rossi, Zhihong Zhang, Lixiang Xu, Edwin R. Hancock

Proceedings of the Structural, Syntactic, and Statistical Pattern Recognition, 2018

A Preliminary Survey of Analyzing Dynamic Time-Varying Financial Networks Using Graph Kernels.

Lixin Cui, Lu Bai, Luca Rossi, Zhihong Zhang, Yuhang Jiao, Edwin R. Hancock

Proceedings of the Structural, Syntactic, and Statistical Pattern Recognition, 2018

A Unified Neighbor Reconstruction Method for Embeddings.

Zhiling Ye, Zhihong Zhang, Lu Bai, Guosheng Hu, Zheng-Jian Bai, Yiqun Hu, Edwin R. Hancock

Proceedings of the 24th International Conference on Pattern Recognition, 2018

Depth-based Subgraph Convolutional Neural Networks.

Chuanyu Xu, Dong Wang, Zhihong Zhang, Beizhan Wang, Da Zhou, Guijun Ren, Lu Bai, Lixin Cui, Edwin R. Hancock

Proceedings of the 24th International Conference on Pattern Recognition, 2018

A Deep Hybrid Graph Kernel Through Deep Learning Networks.

Lixin Cui, Lu Bai, Luca Rossi, Yue Wang, Yuhang Jiao, Edwin R. Hancock

Proceedings of the 24th International Conference on Pattern Recognition, 2018

Deep Co-Investment Network Learning for Financial Assets.

Yue Wang, Chenwei Zhang, Shen Wang, Philip S. Yu, Lu Bai, Lixin Cui

Proceedings of the 2018 IEEE International Conference on Big Knowledge, 2018

Market Abnormality Period Detection via Co-movement Attention Model.

Yue Wang, Chenwei Zhang, Shen Wang, Philip S. Yu, Lu Bai, Lixin Cui

Proceedings of the IEEE International Conference on Big Data (IEEE BigData 2018), 2018

2017

High-order covariate interacted Lasso for feature selection.

Zhihong Zhang, Yiyang Tian, Lu Bai, Jianbing Xiahou, Edwin R. Hancock

Pattern Recognit. Lett., 2017

Quantum kernels for unattributed graphs using discrete-time quantum walks.

Lu Bai, Luca Rossi, Lixin Cui, Zhihong Zhang, Peng Ren, Xiao Bai, Edwin R. Hancock

Pattern Recognit. Lett., 2017

Joint hypergraph learning and sparse regression for feature selection.

Zhihong Zhang, Lu Bai, Yuanheng Liang, Edwin R. Hancock

Pattern Recognit., 2017

Differential weights-based band selection for hyperspectral image classification.

Yun Liu, Chen Wang, Yang Wang, Xiao Bai, Jun Zhou, Lu Bai

Int. J. Wavelets Multiresolution Inf. Process., 2017

Deep Face Model Compression Using Entropy-Based Filter Selection.

Bingbing Han, Zhihong Zhang, Chuanyu Xu, Beizhan Wang, Guosheng Hu, Lu Bai, Qingqi Hong, Edwin R. Hancock

Proceedings of the Image Analysis and Processing - ICIAP 2017, 2017

Adaptive Feature Selection Based on the Most Informative Graph-Based Features.

Lixin Cui, Yuhang Jiao, Lu Bai, Luca Rossi, Edwin R. Hancock

Proceedings of the Graph-Based Representations in Pattern Recognition, 2017

A Nested Alignment Graph Kernel Through the Dynamic Time Warping Framework.

Lu Bai, Luca Rossi, Lixin Cui, Edwin R. Hancock

Proceedings of the Graph-Based Representations in Pattern Recognition, 2017

Fast K-means for Large Scale Clustering.

Qinghao Hu, Jiaxiang Wu, Lu Bai, Yifan Zhang, Jian Cheng

Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, 2017

2016

Fast depth-based subgraph kernels for unattributed graphs.

Lu Bai, Edwin R. Hancock

Pattern Recognit., 2016

Depth-based hypergraph complexity traces from directed line graphs.

Lu Bai, Francisco Escolano, Edwin R. Hancock

Pattern Recognit., 2016

Discriminative sparse representation for face recognition.

Zhihong Zhang, Yuanheng Liang, Lu Bai, Edwin R. Hancock

Multim. Tools Appl., 2016

High-order graph matching kernel for early carcinoma EUS image classification.

Zhihong Zhang, Lu Bai, Peng Ren, Edwin R. Hancock

Multim. Tools Appl., 2016

Maximum margin hashing with supervised information.

Haichuan Yang, Xiao Bai, Yanzhen Liu, Yanyang Wang, Lu Bai, Jun Zhou, Wenzhong Tang

Multim. Tools Appl., 2016

Discriminative sparse neighbor coding.

Xiao Bai, Cheng Yan, Peng Ren, Lu Bai, Jun Zhou

Multim. Tools Appl., 2016

Band Weighting via Maximizing Interclass Distance for Hyperspectral Image Classification.

Cheng Yan, Xiao Bai, Peng Ren, Lu Bai, Wenzhong Tang, Jun Zhou

IEEE Geosci. Remote. Sens. Lett., 2016

P2P Lending Analysis Using the Most Relevant Graph-Based Features.

Lixin Cui, Lu Bai, Yue Wang, Xiao Bai, Zhihong Zhang, Edwin R. Hancock

Proceedings of the Structural, Syntactic, and Statistical Pattern Recognition, 2016

Link prediction via Supervised Dynamic Network Formation.

Yue Wang, Lu Bai

Proceedings of the 23rd International Conference on Pattern Recognition, 2016

Shape classification with a vertex clustering graph kernel.

Lu Bai, Lixin Cui, Yue Wang, Xin Jin, Xiao Bai, Edwin R. Hancock

Proceedings of the 23rd International Conference on Pattern Recognition, 2016

An edge-based matching kernel on commute-time spanning trees.

Lu Bai, Lixin Cui, Francisco Escolano, Edwin R. Hancock

Proceedings of the 23rd International Conference on Pattern Recognition, 2016

A novel entropy-based graph signature from the average mixing matrix.

Lu Bai, Luca Rossi, Lixin Cui, Edwin R. Hancock

Proceedings of the 23rd International Conference on Pattern Recognition, 2016

A transitive aligned Weisfeiler-Lehman subtree kernel.

Lu Bai, Luca Rossi, Lixin Cui, Edwin R. Hancock

Proceedings of the 23rd International Conference on Pattern Recognition, 2016

2015

A quantum Jensen-Shannon graph kernel for unattributed graphs.

Lu Bai, Luca Rossi, Andrea Torsello, Edwin R. Hancock

Pattern Recognit., 2015

A Graph Kernel Based on the Jensen-Shannon Representation Alignment.

Lu Bai, Zhihong Zhang, Chaoyan Wang, Xiao Bai, Edwin R. Hancock

Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

An Aligned Subtree Kernel for Weighted Graphs.

Lu Bai, Luca Rossi, Zhihong Zhang, Edwin R. Hancock

Proceedings of the 32nd International Conference on Machine Learning, 2015

Unsupervised Feature Selection by Graph Optimization.

Zhihong Zhang, Lu Bai, Yuanheng Liang, Edwin R. Hancock

Proceedings of the Image Analysis and Processing - ICIAP 2015, 2015

An Edge-Based Matching Kernel Through Discrete-Time Quantum Walks.

Lu Bai, Zhihong Zhang, Peng Ren, Luca Rossi, Edwin R. Hancock

Proceedings of the Image Analysis and Processing - ICIAP 2015, 2015

Coupled-Feature Hypergraph Representation for Feature Selection.

Zhihong Zhang, Jianbing Xiahou, Lu Bai, Edwin R. Hancock

Proceedings of the Graph-Based Representations in Pattern Recognition, 2015

A Quantum Jensen-Shannon Graph Kernel Using Discrete-Time Quantum Walks.

Lu Bai, Luca Rossi, Peng Ren, Zhihong Zhang, Edwin R. Hancock

Proceedings of the Graph-Based Representations in Pattern Recognition, 2015

Adaptive Graph Learning for Unsupervised Feature Selection.

Zhihong Zhang, Lu Bai, Yuanheng Liang, Edwin R. Hancock

Proceedings of the Computer Analysis of Images and Patterns, 2015

An Edge-Based Matching Kernel for Graphs Through the Directed Line Graphs.

Lu Bai, Zhihong Zhang, Chaoyan Wang, Edwin R. Hancock

Proceedings of the Computer Analysis of Images and Patterns, 2015

A High-Order Depth-Based Graph Matching Method.

Lu Bai, Zhihong Zhang, Peng Ren, Edwin R. Hancock

Proceedings of the Computer Analysis of Images and Patterns, 2015

2014

Information theoretic graph kernels.

Lu Bai

PhD thesis, 2014

Depth-based complexity traces of graphs.

Lu Bai, Edwin R. Hancock

Pattern Recognit., 2014

Transitive State Alignment for the Quantum Jensen-Shannon Kernel.

Andrea Torsello, Andrea Gasparetto, Luca Rossi, Lu Bai, Edwin R. Hancock

Proceedings of the Structural, Syntactic, and Statistical Pattern Recognition, 2014

A Graph Kernel from the Depth-Based Representation.

Lu Bai, Peng Ren, Xiao Bai, Edwin R. Hancock

Proceedings of the Structural, Syntactic, and Statistical Pattern Recognition, 2014

Attributed Graph Kernels Using the Jensen-Tsallis q-Differences.

Lu Bai, Luca Rossi, Horst Bunke, Edwin R. Hancock

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2014

A Hypergraph Kernel from Isomorphism Tests.

Lu Bai, Peng Ren, Edwin R. Hancock

Proceedings of the 22nd International Conference on Pattern Recognition, 2014

Directed Depth-Based Complexity Traces of Hypergraphs from Directed Line Graphs.

Lu Bai, Edwin R. Hancock, Peng Ren, Francisco Escolano

Proceedings of the 22nd International Conference on Pattern Recognition, 2014

An Attributed Graph Kernel from the Jensen-Shannon Divergence.

Lu Bai, Horst Bunke, Edwin R. Hancock

Proceedings of the 22nd International Conference on Pattern Recognition, 2014

Semi-randomized hashing for large scale data retrieval.

Haichuan Yang, Xiao Bai, Jun Zhou, Peng Ren, Jian Cheng, Lu Bai

Proceedings of the International Conference on Data Science and Advanced Analytics, 2014

2013

Graph Kernels from the Jensen-Shannon Divergence.

Lu Bai, Edwin R. Hancock

J. Math. Imaging Vis., 2013

A Fast Jensen-Shannon Subgraph Kernel.

Lu Bai, Edwin R. Hancock

Proceedings of the Image Analysis and Processing - ICIAP 2013, 2013

A Quantum Jensen-Shannon Graph Kernel Using the Continuous-Time Quantum Walk.

Lu Bai, Edwin R. Hancock, Andrea Torsello, Luca Rossi

Proceedings of the Graph-Based Representations in Pattern Recognition, 2013

A Graph Embedding Method Using the Jensen-Shannon Divergence.

Lu Bai, Edwin R. Hancock, Lin Han

Proceedings of the Computer Analysis of Images and Patterns, 2013

2012

A Jensen-Shannon Kernel for Hypergraphs.

Lu Bai, Edwin R. Hancock, Peng Ren

Proceedings of the Structural, Syntactic, and Statistical Pattern Recognition, 2012

Graph Complexity from the Jensen-Shannon Divergence.

Lu Bai, Edwin R. Hancock

Proceedings of the Structural, Syntactic, and Statistical Pattern Recognition, 2012

Sampling graphs from a probabilistic generative model.

Lin Han, Richard C. Wilson, Edwin R. Hancock, Lu Bai, Peng Ren

Proceedings of the 21st International Conference on Pattern Recognition, 2012

Jensen-Shannon graph kernel using information functionals.

Lu Bai, Edwin R. Hancock, Peng Ren

Proceedings of the 21st International Conference on Pattern Recognition, 2012

Graph clustering using graph entropy complexity traces.

Lu Bai, Edwin R. Hancock, Lin Han, Peng Ren

Proceedings of the 21st International Conference on Pattern Recognition, 2012

2011

Graph Clustering Using the Jensen-Shannon Kernel.

Lu Bai, Edwin R. Hancock

Proceedings of the Computer Analysis of Images and Patterns, 2011