A quantum Jensen-Shannon graph kernel using discrete-time quantum walks


Autoria(s): Bai, Lu; Rossi, Luca; Ren, Peng; Zhang, Zhihong; Hancock, Edwin R.
Contribuinte(s)

Liu, Cheng-Lin

Luo, Bin

Kropatsch, Walter G.

Cheng, Jian

Data(s)

2015

Resumo

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.

Formato

application/pdf

Identificador

http://eprints.aston.ac.uk/26704/1/Quantum_Jensen_Shannon_graph_kernel_using_discrete_time_quantum_walks.pdf

Bai, Lu; Rossi, Luca; Ren, Peng; Zhang, Zhihong and Hancock, Edwin R. (2015). A quantum Jensen-Shannon graph kernel using discrete-time quantum walks. IN: Graph-based representations in pattern recognition. Liu, Cheng-Lin; Luo, Bin; Kropatsch, Walter G. and Cheng, Jian (eds) Lecture notes in computer science . Chem (CH): Springer.

Publicador

Springer

Relação

http://eprints.aston.ac.uk/26704/

Tipo

Book Section

NonPeerReviewed