Abstract
In this paper, we develop a new graph kernel by using the quantum Jensen-Shannon divergence and the discrete-time quantum walk. To this end, we commence by performing a discrete-time quantum walk to compute a density matrix over each graph being compared. For a pair of graphs, we compare the mixed quantum states represented by their density matrices using the quantum Jensen-Shannon divergence. With the density matrices for a pair of graphs to hand, the quantum graph kernel between the pair of graphs is defined by exponentiating the negative quantum Jensen-Shannon divergence between the graph density matrices. We evaluate the performance of our kernel on several standard graph datasets, and demonstrate the effectiveness of the new kernel.
Original language | English |
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Title of host publication | Graph-based representations in pattern recognition |
Subtitle of host publication | 10th IAPR-TC-15 international workshop, GbRPR 2015, Beijing, China, May 13-15, 2015. Proceedings |
Editors | Cheng-Lin Liu, Bin Luo, Walter G. Kropatsch, Jian Cheng |
Place of Publication | Chem (CH) |
Publisher | Springer |
Pages | 252-261 |
Number of pages | 10 |
ISBN (Electronic) | 978-3-319-18224-7 |
ISBN (Print) | 978-3-319-18223-0 |
DOIs | |
Publication status | Published - 2015 |
Event | 10th IAPR-TC-15 international workshop, GbRPR 2015 - Beijing, China Duration: 13 May 2015 → 15 May 2015 |
Publication series
Name | Lecture notes in computer science |
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Publisher | Springer |
Volume | 9069 |
ISSN (Print) | 0302-9743 |
ISSN (Electronic) | 1611-3349 |
Workshop
Workshop | 10th IAPR-TC-15 international workshop, GbRPR 2015 |
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Country/Territory | China |
City | Beijing |
Period | 13/05/15 → 15/05/15 |
Bibliographical note
The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-18224-7_25Funding: UK Royal Society