Optimal Representative Distribution Margin Machine for Multi-Instance Learning [PDF]
IEEE Access, 2020 Multi-instance learning (MIL) plays an important role in many real applications, such as image recognition and text classification. The instance-based approach selects instances in each bag to train and has drawn significant attention recently.
Tianxiang Luan +3 more
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Voltage Stability Margin Index Estimation Using a Hybrid Kernel Extreme Learning Machine Approach [PDF]
Energies, 2020 This paper presents a novel approach for Voltage Stability Margin (VSM) estimation that combines a Kernel Extreme Learning Machine (KELM) with a Mean-Variance Mapping Optimization (MVMO) algorithm.
Walter M. Villa-Acevedo +2 more
doaj +4 more sources
Learning the set covering machine by bound minimization and margin-sparsity trade-off [PDF]
Machine Learning, 2009 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
François Laviolette +2 more
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Multiplierless and Sparse Machine Learning based on Margin Propagation Networks. [PDF]
CoRR, 2019 The new generation of machine learning processors have evolved from multi-core and parallel architectures that were designed to efficiently implement matrix-vector-multiplications (MVMs). This is because at the fundamental level, neural network and machine learning operations extensively use MVM operations and hardware compilers exploit the inherent ...
P. M. Nazreen +2 more
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Voltage Stability Margin Estimation Using Machine Learning Tools
Revista Técnica Energía, 2023 Real-time voltage stability assessment, via conventional methods, is a difficult task due to the required large amount of information, high execution times and computational cost. Based on these limitations, this technical work proposes a method for the
Gabriel Guañuna +5 more
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Understanding Generalization in Quantum Machine Learning with Margins [PDF]
CoRRUnderstanding and improving generalization capabilities is crucial for both classical and quantum machine learning (QML). Recent studies have revealed shortcomings in current generalization theories, particularly those relying on uniform bounds, across both classical and quantum settings. In this work, we present a margin-based generalization bound for
Tak Hur, Daniel K. Park
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Optimal Margin Distribution Machine for Multi-Instance Learning [PDF]
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020 Multi-instance learning (MIL) is a celebrated learning framework where each example is represented as a bag of instances. An example is negative if it has no positive instances, and vice versa if at least one positive instance is contained. During the past decades, various MIL algorithms have been proposed, among which the large margin based methods is
Teng Zhang, Hai Jin
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Maxi–Min Margin Machine: Learning Large Margin Classifiers Locally and Globally [PDF]
IEEE Transactions on Neural Networks, 2008 In this paper, we propose a novel large margin classifier, called the maxi-min margin machine M(4). This model learns the decision boundary both locally and globally. In comparison, other large margin classifiers construct separating hyperplanes only either locally or globally. For example, a state-of-the-art large margin classifier, the support vector
Kaizhu Huang, Haiqin Yang, Irwin King
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Intraoperative Assessment of Tumor Margins in Tissue Sections with Hyperspectral Imaging and Machine Learning [PDF]
Cancers, 2022 The intraoperative assessment of tumor margins of head and neck cancer is crucial for complete tumor resection and patient outcome. The current standard is to take tumor biopsies during surgery for frozen section analysis by a pathologist after H&E staining.
David Pertzborn +7 more
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Development of a machine learning-based model for predicting positive margins in high-grade squamous intraepithelial lesion (HSIL) treatment by Cold Knife Conization(CKC): a single-center retrospective study [PDF]
BMC Women's HealthObjectives This study aims to analyze factors associated with positive surgical margins following cold knife conization (CKC) in patients with cervical high-grade squamous intraepithelial lesion (HSIL) and to develop a machine-learning-based risk ...
Lin Zhang +6 more
doaj +2 more sources