Results 31 to 40 of about 21,136,484 (286)

A review of multi-instance learning assumptions [PDF]

, 2010
Multi-instance (MI) learning is a variant of inductive machine learning, where each learning example contains a bag of instances instead of a single feature vector.
Frank, Eibe, Foulds, James Richard
core   +1 more source

DICNet: Deep Instance-Level Contrastive Network for Double Incomplete Multi-View Multi-Label Classification

, 2023
In recent years, multi-view multi-label learning has aroused extensive research enthusiasm. However, multi-view multi-label data in the real world is commonly incomplete due to the uncertain factors of data collection and manual annotation, which means ...
Xu, Yong, Luo, Xiaoling, Huang, Chao, Wu, Zhihao, Liu, Chengliang, Wen, Jie   +5 more
core   +2 more sources

Adaptive Semi-Supervised Classification by Joint Global and Local Graph

IEEE Access, 2019
Recently, semisupervised classification methods have been widely applied in many scientific fields, among them, the graph-based methods of semisupervised classification have attracted great attention due to their effectiveness.
Siyang Deng, Qianqian Wang, Quanxue Gao
doaj   +1 more source

Transductive Multi-View Zero-Shot Learning [PDF]

, 2015
(c) 2012. The copyright of this document resides with its authors.
Yanwei Fu, Tao Xiang, Fu, Y, Timothy M. Hospedales, Hospedales, T, Shaogang Gong, Xiang, T, Hospedales, TM, Gong, S   +8 more
core   +1 more source

Multi-label feature selection based on dynamic graph Laplacian

Tongxin xuebao, 2020
In view of the problems that graph-based multi-label feature selection methods ignore the dynamic change of graph Laplacian matrix, as well as such methods employ logical-value labels to guide feature selection process and loses label information, a ...
Yonghao LI, Liang HU, Ping ZHANG, Wanfu GAO   +3 more
doaj   +2 more sources

Comprehensive Analysis of Mammography Images Using Multi-Branch Attention Convolutional Neural Network

Applied Sciences, 2023
Breast cancer profoundly affects women’s lives; its early diagnosis and treatment increase patient survival chances. Mammography is a common screening method for breast cancer, and many methods have been proposed for automatic diagnosis. However, most of
Ebtihal Al-Mansour, Muhammad Hussain, Hatim A. Aboalsamh, Saad A. Al-Ahmadi   +3 more
doaj   +1 more source

Probabilistic Decision Trees using SVM for Multi-class Classification [PDF]

, 2013
In the automotive repairing backdrop, retrieving from previously solved incident the database features that could support and speed up the diagnostic is of great usefulness.
BOUAMAMA, Karima, MECHBAL, Nazih, Marc Rebillat, Marco Pengov, URIBE, Juan Sebastian, PENGOV, Marco, RÉBILLAT, Marc, Karima Bouamama, Juan Sebastian Uribe, Nazih Mechbal   +9 more
core   +1 more source

A new genetic algorithm for multi-label correlation-based feature selection. [PDF]

, 2015
This paper proposes a new Genetic Algorithm for Multi-Label Correlation-Based Feature Selection (GA-ML-CFS). This GA performs a global search in the space of candidate feature subset, in order to select a high-quality feature subset is used by a multi ...
Jungjit, Suwimol, Freitas, Alex A.
core   +1 more source

Microbiome−host proteostasis crosstalk—An emerging perspective on mechanisms and interventions toward healthy longevity

FEBS Letters, EarlyView.
Proteostasis and the gut microbiota play a key role in shaping host physiology. Microbiota‐derived metabolites, vitamins, and RNA modulate host proteostasis. Findings from model systems, including C. elegans, indicate microbes can either stabilize or disrupt host proteostasis.
Abhishek Anil Dubey, Maria Ermolaeva
wiley   +1 more source

Incomplete multi–view partial multi–label learning network with structure–aware consistent fusion

Journal of King Saud University: Computer and Information Sciences
In recent years, incomplete multi-view partial multi-label classification has attracted growing attention due to its practical relevance. However, many existing methods rely on equal-weight (average) fusion and thus overlook sample-wise reliability ...
Xingang Mao, Yang Xu, Wenbin Bu, Zherui Yang   +3 more
doaj   +1 more source