Results 11 to 20 of about 414,528 (301)
Unsupervised Machine Learning for Networking: Techniques, Applications and Research Challenges
IEEE Access, 2019 While machine learning and artificial intelligence have long been applied in networking research, the bulk of such works has focused on supervised learning.
Muhammad Usama +7 more
doaj +3 more sources
DeConFuse: a deep convolutional transform-based unsupervised fusion framework
EURASIP Journal on Advances in Signal Processing, 2020 This work proposes an unsupervised fusion framework based on deep convolutional transform learning. The great learning ability of convolutional filters for data analysis is well acknowledged.
Pooja Gupta +4 more
doaj +1 more source
Classification under Streaming Emerging New Classes: A Solution using Completely Random Trees [PDF]
, 2016 This paper investigates an important problem in stream mining, i.e., classification under streaming emerging new classes or SENC. The common approach is to treat it as a classification problem and solve it using either a supervised learner or a semi ...
Mu, Xin, Ting, Kai Ming, Zhou, Zhi-Hua
core +3 more sources
Unsupervised Learning via Total Correlation Explanation [PDF]
, 2017 Learning by children and animals occurs effortlessly and largely without obvious supervision. Successes in automating supervised learning have not translated to the more ambiguous realm of unsupervised learning where goals and labels are not provided ...
Steeg, Greg Ver
core +1 more source
Total Denoising: Unsupervised Learning of 3D Point Cloud Cleaning [PDF]
, 2019 We show that denoising of 3D point clouds can be learned unsupervised, directly from noisy 3D point cloud data only. This is achieved by extending recent ideas from learning of unsupervised image denoisers to unstructured 3D point clouds.
Hermosilla, Pedro +2 more
core +2 more sources
IEEE Access, 2021 Efficient modeling of high-dimensional data requires extracting only relevant dimensions through feature learning. Unsupervised feature learning has gained tremendous attention due to its unbiased approach, no need for prior knowledge or expensive manual
Chathurika S. Wickramasinghe +2 more
doaj +1 more source
Breast Image Classification Based on Multi-feature Joint Supervised Dictionary Learning [PDF]
Jisuanji gongcheng, 2018 Aiming at the problem that the unsupervised dictionary learning algorithm has low image classification accuracy,a supervised dictionary learning classification algorithm which combines with multiple image features is proposed.It uses the convolution ...
LIU Lihui,XU Jun,GONG Lei
doaj +1 more source
Applied Sciences, 2022 Supervised image denoising methods based on deep neural networks require a large amount of noisy-clean or noisy image pairs for network training. Thus, their performance drops drastically when the given noisy image is significantly different from the ...
Shaoping Xu +5 more
doaj +1 more source
Memristor Neural Network Training with Clock Synchronous Neuromorphic System
Micromachines, 2019 Memristor devices are considered to have the potential to implement unsupervised learning, especially spike timing-dependent plasticity (STDP), in the field of neuromorphic hardware research.
Sumin Jo +5 more
doaj +1 more source
Unsupervised online multitask learning of behavioral sentence embeddings [PDF]
PeerJ Computer Science, 2019 Appropriate embedding transformation of sentences can aid in downstream tasks such as NLP and emotion and behavior analysis. Such efforts evolved from word vectors which were trained in an unsupervised manner using large-scale corpora.
Shao-Yen Tseng +2 more
doaj +2 more sources