Lu Bai (Associate Professor)
Lu Bai (Associate Professor)
Central University of Finance and Economics, Beijing, China; University of York, York, UK
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Cited by
Cited by
Graph kernels from the jensen-shannon divergence
L Bai, ER Hancock
Journal of mathematical imaging and vision 47 (1), 60-69, 2013
A quantum jensen–shannon graph kernel for unattributed graphs
L Bai, L Rossi, A Torsello, ER Hancock
Pattern Recognition 48 (2), 344-355, 2015
Joint hypergraph learning and sparse regression for feature selection
Z Zhang, L Bai, Y Liang, E Hancock
Pattern Recognition 63, 291-309, 2017
Adaptive hash retrieval with kernel based similarity
X Bai, C Yan, H Yang, L Bai, J Zhou, ER Hancock
Pattern Recognition 75, 136-148, 2018
An aligned subtree kernel for weighted graphs
L Bai, L Rossi, Z Zhang, E Hancock
International Conference on Machine Learning, 30-39, 2015
Depth-based complexity traces of graphs
L Bai, ER Hancock
Pattern Recognition 47 (3), 1172-1186, 2014
Attributed Graph Kernels Using the Jensen-Tsallis q-Differences
L Bai, L Rossi, H Bunke, ER Hancock
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2014
Nonlocal similarity based nonnegative tucker decomposition for hyperspectral image denoising
X Bai, F Xu, L Zhou, Y Xing, L Bai, J Zhou
IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2018
Quantum-based subgraph convolutional neural networks
Z Zhang, D Chen, J Wang, L Bai, ER Hancock
Pattern Recognition 88, 38-49, 2019
Fast depth-based subgraph kernels for unattributed graphs
L Bai, ER Hancock
Pattern Recognition 50, 233-245, 2016
Quantum kernels for unattributed graphs using discrete-time quantum walks
L Bai, L Rossi, L Cui, Z Zhang, P Ren, X Bai, E Hancock
Pattern Recognition Letters 87, 96-103, 2017
Band weighting via maximizing interclass distance for hyperspectral image classification
C Yan, X Bai, P Ren, L Bai, W Tang, J Zhou
IEEE Geoscience and Remote Sensing Letters 13 (7), 922-925, 2016
A hypergraph kernel from isomorphism tests
L Bai, P Ren, ER Hancock
2014 22nd International Conference on Pattern Recognition, 3880-3885, 2014
Depth-based hypergraph complexity traces from directed line graphs
L Bai, F Escolano, ER Hancock
Pattern Recognition 54, 229-240, 2016
A graph kernel based on the jensen-shannon representation alignment
L Bai, Z Zhang, C Wang, X Bai, E Hancock
Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015
Depth-based subgraph convolutional auto-encoder for network representation learning
Z Zhang, D Chen, Z Wang, H Li, L Bai, ER Hancock
Pattern Recognition 90, 363-376, 2019
A graph kernel from the depth-based representation
L Bai, P Ren, X Bai, ER Hancock
Joint IAPR International Workshops on Statistical Techniques in Pattern …, 2014
Learning backtrackless aligned-spatial graph convolutional networks for graph classification
L Bai, L Cui, Y Jiao, L Rossi, E Hancock
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2020
A quantum-inspired similarity measure for the analysis of complete weighted graphs
L Bai, L Rossi, L Cui, J Cheng, ER Hancock
IEEE transactions on cybernetics 50 (3), 1264-1277, 2019
A quantum jensen-shannon graph kernel using the continuous-time quantum walk
L Bai, ER Hancock, A Torsello, L Rossi
International Workshop on Graph-Based Representations in Pattern Recognition …, 2013
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