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research-article

Double similarities weighted multi-instance learning kernel and its application

Authors:

Wen ZhengAuthors Info & Claims

Volume 238, Issue PB

https://doi.org/10.1016/j.eswa.2023.121900

Published: 15 March 2024 Publication History

Abstract

Multi-instance learning (MIL), as a special version of classification, focuses on labeled sets (bags) consisting of unlabeled instances and has drawn accumulative attention due to its significant importance in practical applications. However, most existing MIL methods just utilize partial information (bags or instances) of MIL data to construct the kernel function, resulting in deteriorated classification performance of MIL. In this paper, we propose a Double Similarities weighted Multi-Instance Learning (DSMIL) kernel framework, which utilizes the similarities of Bag-to-Bag (B2B) and Instance-to-Bag (I2B). In the proposed kernel framework, the similarities of B2B and I2B could be derived from the prototypes distance of inter-bag and similarity matrix of intra-bag, respectively, based on the affinity propagation (AP) clustering of the bag. Meanwhile, we give theoretical proof of the validity of the designed kernel function. Experimental results on benchmark and semi-synthetic datasets show that our proposed method obtains competitive classification performance and achieves robustness to parameters and noise.

Highlights

•

A double similarities weighted MIL kernel is proposed and proved as a valid kernel.

•

The DSMIL integrates the similarities of B2B and I2B into the kernel function.

•

The DSMIL obtains competitive results on benchmark datasets and newsgroups dataset.

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Cited By

Yang MChen TWu WZeng WZhang JMin F(2025)Dual-perspective multi-instance embedding learning with adaptive density distribution miningPattern Recognition10.1016/j.patcog.2024.111063158:COnline publication date: 1-Feb-2025
https://dl.acm.org/doi/10.1016/j.patcog.2024.111063
Yang MZhang JPan ZMin F(2025)Multi-instance embedding space set-kernel fusion with discriminability metricApplied Intelligence10.1007/s10489-024-06160-z55:6Online publication date: 1-Apr-2025
https://dl.acm.org/doi/10.1007/s10489-024-06160-z

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Information & Contributors

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Published In

cover image Expert Systems with Applications: An International Journal

Expert Systems with Applications: An International Journal Volume 238, Issue PB

Mar 2024

1583 pages

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Elsevier Ltd.

Publisher

Pergamon Press, Inc.

United States

Publication History

Published: 15 March 2024

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Cited By

Yang MChen TWu WZeng WZhang JMin F(2025)Dual-perspective multi-instance embedding learning with adaptive density distribution miningPattern Recognition10.1016/j.patcog.2024.111063158:COnline publication date: 1-Feb-2025
https://dl.acm.org/doi/10.1016/j.patcog.2024.111063
Yang MZhang JPan ZMin F(2025)Multi-instance embedding space set-kernel fusion with discriminability metricApplied Intelligence10.1007/s10489-024-06160-z55:6Online publication date: 1-Apr-2025
https://dl.acm.org/doi/10.1007/s10489-024-06160-z

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