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IEEE/ACM Transactions on Networking, ISSN 1063-6692, 08/2015, Volume 23, Issue 4, pp. 1257 - 1270
As a fundamental tool for network management and security, traffic classification has attracted increasing attention in recent years. A significant challenge... 
Training | Correlation | Semi-supervised learning | Clustering algorithms | Ports (Computers) | zero-day applications | Robustness | IP networks | traffic classification | Payloads | COMPUTER SCIENCE, HARDWARE & ARCHITECTURE | COMPUTER SCIENCE, THEORY & METHODS | TELECOMMUNICATIONS | IDENTIFICATION | ENGINEERING, ELECTRICAL & ELECTRONIC
Journal Article
IEEE Transactions on Image Processing, ISSN 1057-7149, 12/2017, Volume 26, Issue 12, pp. 5718 - 5729
In many practical applications, there are a great number of unlabeled samples available, while labeling them is a costly and tedious process. Therefore, how to... 
Training | Additives | Multiview data | Supervised learning | Optimization methods | Semisupervised learning | Feature extraction | Data mining | semi-supervised classification | weight learning | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | ENGINEERING, ELECTRICAL & ELECTRONIC | Usage | Artificial intelligence | Mathematical optimization | Statistical sampling
Journal Article
IEEE Transactions on Neural Networks and Learning Systems, ISSN 2162-237X, 11/2013, Volume 24, Issue 11, pp. 1763 - 1772
Journal Article
Information Sciences, ISSN 0020-0255, 03/2019, Volume 477, pp. 15 - 29
The purpose of document classification is to assign the most appropriate label to a specified document. The main challenges in document classification are... 
LDA | Co-training | Semi-supervised learning | TF–IDF | Document classification | Doc2vec | TF-IDF | FREQUENCY | COMPUTER SCIENCE, INFORMATION SYSTEMS | TEXT
Journal Article
Annals of Operations Research, ISSN 0254-5330, 5/2019, Volume 276, Issue 1, pp. 249 - 266
Journal Article
Neural Networks, ISSN 0893-6080, 11/2012, Volume 35, pp. 46 - 53
Journal Article
Neurocomputing, ISSN 0925-2312, 06/2012, Volume 86, pp. 75 - 85
Co-training is a well-known semi-supervised learning technique that applies two basic learners to train the data source, which uses the most confident... 
Co-training | Semi-supervised learning | Class probability estimation | Machine learning | Classification | Diversity | IMAGE RETRIEVAL | EM ALGORITHM | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | CLASSIFIERS | PROBABILITIES | Learning | Training | Trains | Labels | Data sources | Cobalt
Journal Article
Neurocomputing, ISSN 0925-2312, 09/2019
Journal Article
IEEE Transactions on Image Processing, ISSN 1057-7149, 02/2013, Volume 22, Issue 2, pp. 523 - 536
Journal Article
Applied Soft Computing Journal, ISSN 1568-4946, 06/2019, Volume 79, pp. 46 - 58
Graph-based semi-supervised classification (GSSC) takes labeled and unlabeled samples as vertices in a graph, and edge weights as the similarity between... 
Weighted samples | Hard-to-cluster index | Semi-supervised classification | Graph optimization | GRAPH | COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS | SPARSE REPRESENTATION | FRAMEWORK | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | Information science | Analysis
Journal Article
Pattern Recognition, ISSN 0031-3203, 09/2016, Volume 57, pp. 179 - 189
Journal Article
Neurocomputing, ISSN 0925-2312, 04/2019, Volume 337, pp. 120 - 128
Target-oriented aspect-based sentiment analysis (TABSA) is a sentiment classification task that requires performing fine-grained semantical reasoning about a... 
Sentiment analysis | Variational inference | Semi-supervised learning | Generative model | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | Computer science | Analysis
Journal Article