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Home / Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence, 32

Nonlinear Pairwise Layer and Its Training for Kernel Learning

March 15, 2023

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Published Date: 2018-02-08

Registration: ISSN 2374-3468 (Online) ISSN 2159-5399 (Print)

Copyright: Published by AAAI Press, Palo Alto, California USA Copyright © 2018, Association for the Advancement of Artificial Intelligence All Rights Reserved.

Authors

Fanghui Liu

Shanghai Jiao Tong University


Xiaolin Huang

Shanghai Jiao Tong University


Chen Gong

Nanjing University of Science and Technology


Jie Yang

Shanghai Jiao Tong University


Li Li

Tsinghua University


DOI:

10.1609/aaai.v32i1.11622


Abstract:

Kernel learning is a fundamental technique that has been intensively studied in the past decades. For the complicated practical tasks, the traditional "shallow" kernels (e.g., Gaussian kernel and sigmoid kernel) are not flexible enough to produce satisfactory performance. To address this shortcoming, this paper introduces a nonlinear layer in kernel learning to enhance the model flexibility. This layer is pairwise, which fully considers the coupling information among examples. So our model contains a fixed single mapping layer (i.e. a Gaussian kernel) as well as a nonlinear pairwise layer, thereby achieving better flexibility than the existing kernel structures. Moreover, the proposed structure can be seamlessly embedded to Support Vector Machines (SVM), of which the training process can be formulated as a joint optimization problem including nonlinear function learning and standard SVM optimization. We theoretically prove that the objective function is gradient-Lipschitz continuous, which further guides us how to accelerate the optimization process in a deep kernel architecture. Experimentally, we find that the proposed structure outperforms other state-ofthe-art kernel-based algorithms on various benchmark datasets, and thus the effectiveness of the incorporated pairwise layer with its training approach is demonstrated.

Topics: AAAI

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HOW TO CITE:

Fanghui Liu||Xiaolin Huang||Chen Gong||Jie Yang||Li Li Nonlinear Pairwise Layer and Its Training for Kernel Learning Proceedings of the AAAI Conference on Artificial Intelligence, 32 (2018) .

Fanghui Liu||Xiaolin Huang||Chen Gong||Jie Yang||Li Li Nonlinear Pairwise Layer and Its Training for Kernel Learning AAAI 2018, .

Fanghui Liu||Xiaolin Huang||Chen Gong||Jie Yang||Li Li (2018). Nonlinear Pairwise Layer and Its Training for Kernel Learning. Proceedings of the AAAI Conference on Artificial Intelligence, 32, .

Fanghui Liu||Xiaolin Huang||Chen Gong||Jie Yang||Li Li. Nonlinear Pairwise Layer and Its Training for Kernel Learning. Proceedings of the AAAI Conference on Artificial Intelligence, 32 2018 p..

Fanghui Liu||Xiaolin Huang||Chen Gong||Jie Yang||Li Li. 2018. Nonlinear Pairwise Layer and Its Training for Kernel Learning. "Proceedings of the AAAI Conference on Artificial Intelligence, 32". .

Fanghui Liu||Xiaolin Huang||Chen Gong||Jie Yang||Li Li. (2018) "Nonlinear Pairwise Layer and Its Training for Kernel Learning", Proceedings of the AAAI Conference on Artificial Intelligence, 32, p.

Fanghui Liu||Xiaolin Huang||Chen Gong||Jie Yang||Li Li, "Nonlinear Pairwise Layer and Its Training for Kernel Learning", AAAI, p., 2018.

Fanghui Liu||Xiaolin Huang||Chen Gong||Jie Yang||Li Li. "Nonlinear Pairwise Layer and Its Training for Kernel Learning". Proceedings of the AAAI Conference on Artificial Intelligence, 32, 2018, p..

Fanghui Liu||Xiaolin Huang||Chen Gong||Jie Yang||Li Li. "Nonlinear Pairwise Layer and Its Training for Kernel Learning". Proceedings of the AAAI Conference on Artificial Intelligence, 32, (2018): .

Fanghui Liu||Xiaolin Huang||Chen Gong||Jie Yang||Li Li. Nonlinear Pairwise Layer and Its Training for Kernel Learning. AAAI[Internet]. 2018[cited 2023]; .


ISSN: 2374-3468


Published by AAAI Press, Palo Alto, California USA
Copyright 2022, Association for the Advancement of
Artificial Intelligence 1900 Embarcadero Road, Suite
101, Palo Alto, California 94303 All Rights Reserved

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