Multiple Instance Learning via Semi-supervised Laplacian TSVM
Sign Up to like & getrecommendations! Published in 2017 at "Neural Processing Letters"
DOI: 10.1007/s11063-017-9579-5
Abstract: Multiple instance learning attempts to learn from a training set consists of labeled bags each containing many unlabeled instances. In previous works, most existing algorithms mainly pay attention to the ‘most positive’ instance in each… read more here.
Keywords: instance learning; semi supervised; multiple instance; via semi ... See more keywords
Multiple instance learning for sequence data with across bag dependencies
Sign Up to like & getrecommendations! Published in 2020 at "International Journal of Machine Learning and Cybernetics"
DOI: 10.1007/s13042-019-01021-5
Abstract: In Multiple Instance Learning (MIL) problem for sequence data, the instances inside the bags are sequences. In some real world applications such as bioinformatics, comparing a random couple of sequences makes no sense. In fact,… read more here.
Keywords: instance learning; multiple instance; sequence data; across bag ... See more keywords
Computational modeling of in vivo and in vitro protein‐DNA interactions by multiple instance learning
Sign Up to like & getrecommendations! Published in 2017 at "Bioinformatics"
DOI: 10.1093/bioinformatics/btx115
Abstract: Motivation: The study of transcriptional regulation is still difficult yet fundamental in molecular biology research. While the development of both in vivo and in vitro profiling techniques have significantly enhanced our knowledge of transcription factor… read more here.
Keywords: vivo vitro; dna interactions; instance learning; dna ... See more keywords
Deep Feature Fusion Multiple Instance Learning for WaDang Recognition
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Access"
DOI: 10.1109/access.2019.2929837
Abstract: WaDang recognition can provide valuable information for digital protection of cultural relics. However, WaDang recognition is challenging due to a great number of variations, such as different characters, different background pattern, and different scale and… read more here.
Keywords: multiple instance; deep feature; instance learning; recognition ... See more keywords
Optimal Representative Distribution Margin Machine for Multi-Instance Learning
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Access"
DOI: 10.1109/access.2020.2988764
Abstract: 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. However,… read more here.
Keywords: margin; instance; instance learning; distribution ... See more keywords
Leveraging Unlabelled Data in Multiple-Instance Learning Problems for Improved Detection of Parkinsonian Tremor in Free-Living Conditions
Sign Up to like & getrecommendations! Published in 2023 at "IEEE journal of biomedical and health informatics"
DOI: 10.1109/jbhi.2023.3267095
Abstract: Data-driven approaches for remote detection of Parkinson's Disease and its motor symptoms have proliferated in recent years, owing to the potential clinical benefits of early diagnosis. The holy grail of such approaches is the free-living… read more here.
Keywords: multiple instance; detection; instance learning; instance ... See more keywords
Multiple Instance Learning With Random Forest for Event Logs Analysis and Predictive Maintenance in Ship Electric Propulsion System
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Industrial Informatics"
DOI: 10.1109/tii.2022.3144177
Abstract: In this article, a novel weakly supervised machine learning approach is proposed for intelligent predictive maintenance (IPdM). It employs balanced random forest and multiple instance learning based on event logs from ships’ electric propulsion systems.… read more here.
Keywords: propulsion; multiple instance; event logs; instance learning ... See more keywords
A Structure-aware Hierarchical Graph-based Multiple Instance Learning Framework for pT Staging in Histopathological Image.
Sign Up to like & getrecommendations! Published in 2023 at "IEEE transactions on medical imaging"
DOI: 10.1109/tmi.2023.3273236
Abstract: Pathological primary tumor (pT) stage focuses on the infiltration degree of the primary tumor to surrounding tissues, which relates to the prognosis and treatment choices. The pT staging relies on the field-of-views from multiple magnifications… read more here.
Keywords: structure aware; hierarchical graph; instance learning; graph based ... See more keywords
Scalable Algorithms for Multi-Instance Learning
Sign Up to like & getrecommendations! Published in 2017 at "IEEE Transactions on Neural Networks and Learning Systems"
DOI: 10.1109/tnnls.2016.2519102
Abstract: Multi-instance learning (MIL) has been widely applied to diverse applications involving complicated data objects, such as images and genes. However, most existing MIL algorithms can only handle small- or moderate-sized data. In order to deal… read more here.
Keywords: instance learning; multi instance; mil; mil algorithms ... See more keywords
A Semiproximal Support Vector Machine Approach for Binary Multiple Instance Learning
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Transactions on Neural Networks and Learning Systems"
DOI: 10.1109/tnnls.2020.3015442
Abstract: We face a binary multiple instance learning (MIL) problem, whose objective is to discriminate between two kinds of point sets: positive and negative. In the MIL terminology, such sets are called bags, and the points… read more here.
Keywords: vector machine; multiple instance; instance; binary multiple ... See more keywords
Dual-Stream Multiple Instance Learning for Depression Detection With Facial Expression Videos
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Neural Systems and Rehabilitation Engineering"
DOI: 10.1109/tnsre.2022.3204757
Abstract: Depression is a common mental illness which has brought great harm to the individuals. With recent evidence that many objective physiological signals are associated with depression, automated detection of depression is urgent and important for… read more here.
Keywords: multiple instance; depression; instance learning; detection ... See more keywords