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Information Sciences, ISSN 0020-0255, 10/2014, Volume 281, pp. 674 - 686
How do we accurately browse a large set of images or efficiently annotate the images from an image library? Image clustering methods are invaluable tools for... 
Pairwise constraints | Manifold structure | Semantic distance metric | Clustering | SEMI-SUPERVISED RANKING | FUSION | RECOGNITION | COMPUTER SCIENCE, INFORMATION SYSTEMS | CLASSIFICATION | RETRIEVAL | FEATURES | IMAGE | COLOR | SIMILARITY | SCENE | Distance education | Learning | Histograms | Construction | Semantics | Images | Visual | Preserving
Journal Article
IEEE Transactions on Multimedia, ISSN 1520-9210, 11/2015, Volume 17, Issue 11, pp. 1989 - 1999
Recent years have witnessed the explosive growth of community-contributed images with rich context information, which is beneficial to the task of image... 
Learning systems | Visualization | metric learning | Semantics | Image retrieval | Data structures | Noise measurement | Deep | weakly supervised | image retrieval | COMPUTER SCIENCE, SOFTWARE ENGINEERING | DIMENSIONALITY REDUCTION | COMPUTER SCIENCE, INFORMATION SYSTEMS | TELECOMMUNICATIONS | Optimization | Learning | Retrieval | Algorithms | Images | Tags | Visual
Journal Article
Pattern Recognition, ISSN 0031-3203, 12/2019, Volume 96, p. 106994
Measuring distance among data point pairs is a necessary step among numerous counts of algorithms in machine learning, pattern recognition and data mining. In... 
Local algorithm | Multimodal data | Linear metric learning | Neighborhood learning | Supervised metric learning | DIMENSIONALITY REDUCTION | FACE | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | ENGINEERING, ELECTRICAL & ELECTRONIC
Journal Article
International Journal of Computer Vision, ISSN 0920-5691, 8/2018, Volume 126, Issue 8, pp. 855 - 874
Journal Article
Neurocomputing, ISSN 0925-2312, 11/2019
Journal Article
IEICE Transactions on Information and Systems, ISSN 0916-8532, 2019, Volume E102.D, Issue 3, pp. 568 - 578
Network embedding has attracted an increasing amount of attention in recent years due to its wide-ranging applications in graph mining tasks such as vertex... 
network representation learning | anchor initialization | deep metric learning | semi-supervised learning | likelihood label | COMPUTER SCIENCE, SOFTWARE ENGINEERING | COMPUTER SCIENCE, INFORMATION SYSTEMS | Learning | Anchors | Visualization | Algorithms | Apexes | Classification | Embedding | Labels | Representations | Scientific visualization
Journal Article
Pattern Recognition, ISSN 0031-3203, 2010, Volume 43, Issue 4, pp. 1320 - 1333
Most existing representative works in semi-supervised clustering do not sufficiently solve the violation problem of pairwise constraints. On the other hand,... 
Semi-supervised clustering | Pairwise constraint | Metric learning | Closure centroid | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | ENGINEERING, ELECTRICAL & ELECTRONIC | Computer science | Analysis | Methods
Journal Article
IEEE Access, ISSN 2169-3536, 2016, Volume 4, pp. 8558 - 8571
Journal Article
IEEE Transactions on Intelligent Transportation Systems, ISSN 1524-9050, 05/2016, Volume 17, Issue 5, pp. 1415 - 1427
Journal Article
IEEE Transactions on Neural Networks and Learning Systems, ISSN 2162-237X, 10/2019, Volume 30, Issue 10, pp. 3084 - 3095
Journal Article
IEEE Transactions on Image Processing, ISSN 1057-7149, 02/2019, Volume 28, Issue 2, pp. 739 - 754
Journal Article
Neurocomputing, ISSN 0925-2312, 01/2018, Volume 275, pp. 394 - 402
Partial label learning (PLL) is a new weakly supervised learning framework that addresses the classification problems, where the true label of each training... 
Weakly supervised data | Weighted geometric mean | Partial label learning | Metric learning | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Journal Article
Knowledge-Based Systems, ISSN 0950-7051, 11/2012, Volume 35, pp. 304 - 311
Existing methods for semi-supervised fuzzy c-means (FCMs) suffer from the following issues: (1) the Euclidean distance tends to work poorly if each feature of... 
Semi-supervised clustering | Pairwise constraint | Prior membership degree | Maximum entropy | Metric learning | DISTANCE | C-MEANS | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | Algorithms
Journal Article
Pattern Recognition, ISSN 0031-3203, 09/2013, Volume 46, Issue 9, pp. 2576 - 2587
Learning an appropriate distance metric is a critical problem in pattern recognition. This paper addresses the problem of semi-supervised metric learning. We... 
Topology preserving | Semi-supervised assumptions | Semi-supervised metric learning | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | ENGINEERING, ELECTRICAL & ELECTRONIC | Computer science | Distance education | Algorithms | Learning | Manifolds | Classification | Clusters | Pattern recognition | Topology | Smoothness | Density
Journal Article
Information Sciences, ISSN 0020-0255, 03/2018, Volume 429, pp. 260 - 283
Hyperspectral images provide a precise representation of the earth’s surface, with abundant spectral and spatial features, but normal classification algorithms... 
Kernel-based segmentation | Mahalanobis kernel | Supervised learning | Hyperspectral classification | ENERGY MINIMIZATION | FEATURE-EXTRACTION | SEGMENTATION | COMPUTER SCIENCE, INFORMATION SYSTEMS | SYSTEMS | GRAPH CUTS | ALGORITHMS | Distance education | Analysis | Algorithms
Journal Article
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), ISSN 0302-9743, 2019, Volume 11448, pp. 383 - 386
Conference Proceeding
Statistical Analysis and Data Mining: The ASA Data Science Journal, ISSN 1932-1864, 04/2016, Volume 9, Issue 2, pp. 117 - 134
This paper proposes a boosting‐based solution addressing metric learning problems for high‐dimensional data. Distance measures have been used as natural... 
boosting | supervised learning | sparsity | Sparsity | Supervised learning | Boosting | STATISTICS & PROBABILITY | COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | Distance education | Analysis
Journal Article
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