Selection of relevant features and examples in machine learning
Artificial Intelligence - Special issue on relevance
Wrappers for feature subset selection
Artificial Intelligence - Special issue on relevance
Feature Selection for Knowledge Discovery and Data Mining
Feature Selection for Knowledge Discovery and Data Mining
AnnoSearch: Image Auto-Annotation by Search
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Image annotation by large-scale content-based image retrieval
MULTIMEDIA '06 Proceedings of the 14th annual ACM international conference on Multimedia
MULTIMEDIA '06 Proceedings of the 14th annual ACM international conference on Multimedia
Capabilities of outlier detection schemes in large datasets, framework and methodologies
Knowledge and Information Systems
The Journal of Machine Learning Research
Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Examples
The Journal of Machine Learning Research
Supervised Learning of Semantic Classes for Image Annotation and Retrieval
IEEE Transactions on Pattern Analysis and Machine Intelligence
Label Propagation through Linear Neighborhoods
IEEE Transactions on Knowledge and Data Engineering
Image retrieval: Ideas, influences, and trends of the new age
ACM Computing Surveys (CSUR)
Annotating Images by Mining Image Search Results
IEEE Transactions on Pattern Analysis and Machine Intelligence
The MIR flickr retrieval evaluation
MIR '08 Proceedings of the 1st ACM international conference on Multimedia information retrieval
ICDM '08 Proceedings of the 2008 Eighth IEEE International Conference on Data Mining
Linear Neighborhood Propagation and Its Applications
IEEE Transactions on Pattern Analysis and Machine Intelligence
Inferring semantic concepts from community-contributed images and noisy tags
MM '09 Proceedings of the 17th ACM international conference on Multimedia
NUS-WIDE: a real-world web image database from National University of Singapore
Proceedings of the ACM International Conference on Image and Video Retrieval
Exact Matrix Completion via Convex Optimization
Foundations of Computational Mathematics
Learning with l1-graph for image analysis
IEEE Transactions on Image Processing
Unsupervised feature selection for multi-cluster data
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
Efficient large-scale image annotation by probabilistic collaborative multi-label propagation
Proceedings of the international conference on Multimedia
Image tag refinement towards low-rank, content-tag prior and error sparsity
Proceedings of the international conference on Multimedia
A Singular Value Thresholding Algorithm for Matrix Completion
SIAM Journal on Optimization
LIBSVM: A library for support vector machines
ACM Transactions on Intelligent Systems and Technology (TIST)
Towards multi-semantic image annotation with graph regularized exclusive group lasso
MM '11 Proceedings of the 19th ACM international conference on Multimedia
Exploiting the entire feature space with sparsity for automatic image annotation
MM '11 Proceedings of the 19th ACM international conference on Multimedia
Recovering Low-Rank and Sparse Components of Matrices from Incomplete and Noisy Observations
SIAM Journal on Optimization
Tag localization with spatial correlations and joint group sparsity
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
Web and Personal Image Annotation by Mining Label Correlation With Relaxed Visual Graph Embedding
IEEE Transactions on Image Processing
Saliency Detection by Multitask Sparsity Pursuit
IEEE Transactions on Image Processing
Multi-label visual classification with label exclusive context
ICCV '11 Proceedings of the 2011 International Conference on Computer Vision
RASL: Robust Alignment by Sparse and Low-Rank Decomposition for Linearly Correlated Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Robust Recovery of Subspace Structures by Low-Rank Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
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Graph-based semi-supervised image annotation has achieved great success in a variety of studies, yet it essentially and intuitively suffers from both the irrelevant/noisy features (referred to as feature outliers) and the unusual/corrupted samples (referred to as sample outliers). In this work, we investigate how to derive robust sample affinity matrix via simultaneous feature and sample outlier pursuit. This task is formulated as a Dual-outlier and Prior-driven Low-Rank Representation (DP-LRR) problem, which possesses convexity in objective function. In DP-LRR, the clean data are assumed to be self-reconstructible with low-rank coefficient matrix as in LRR; while the error matrix is decomposed as the sum of a row-wise sparse matrix and a column-wise sparse matrix, the ℓ2,1-norm minimization of which encourages the pursuit of feature and sample outliers respectively. The DP-LRR is further regularized by the priors from side information, that is, the inhomogeneous data pairs. An efficient iterative procedure based on linearized alternating direction method is presented to solve the DP-LRR problem, with closed-form solutions within each iteration. The derived low-rank reconstruction coefficient matrix is then fed into any graph based semi-supervised label propagation algorithm for image annotation, and as a by-product, the cleaned data from DP-LRR can also be utilized as a better image representation to generally boost image annotation performance. Extensive experiments on MIRFlickr, Corel30K, NUS-WIDE-LITE and NUS-WIDE databases well demonstrate the effectiveness of the proposed formulation for robust image annotation.