Saliency, Scale and Image Description
International Journal of Computer Vision
Laplacian Eigenmaps for dimensionality reduction and data representation
Neural Computation
Object Recognition from Local Scale-Invariant Features
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
The Journal of Machine Learning Research
Image Categorization by Learning and Reasoning with Regions
The Journal of Machine Learning Research
Learning Object Categories from Google"s Image Search
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
Topic modeling with network regularization
Proceedings of the 17th international conference on World Wide Web
Opinion integration through semi-supervised topic modeling
Proceedings of the 17th international conference on World Wide Web
Graph-based multiple-instance learning for object-based image retrieval
MIR '08 Proceedings of the 1st ACM international conference on Multimedia information retrieval
Linear Neighborhood Propagation and Its Applications
IEEE Transactions on Pattern Analysis and Machine Intelligence
Human Action Recognition by Semilatent Topic Models
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
Semi-supervised topic modeling for image annotation
MM '09 Proceedings of the 17th ACM international conference on Multimedia
Correlative linear neighborhood propagation for video annotation
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Exact Matrix Completion via Convex Optimization
Foundations of Computational Mathematics
Image Classification via Semi-supervised pLSA
ICIG '09 Proceedings of the 2009 Fifth International Conference on Image and Graphics
Learning with l1-graph for image analysis
IEEE Transactions on Image Processing
Matrix Completion from Noisy Entries
The Journal of Machine Learning Research
A Singular Value Thresholding Algorithm for Matrix Completion
SIAM Journal on Optimization
Summarizing tourist destinations by mining user-generated travelogues and photos
Computer Vision and Image Understanding
Semi-supervised Classification via Low Rank Graph
ICIG '11 Proceedings of the 2011 Sixth International Conference on Image and Graphics
Image Annotation by Graph-Based Inference With Integrated Multiple/Single Instance Representations
IEEE Transactions on Multimedia
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Topic model is a popular tool for visual concept learning. Most topic models are either unsupervised or fully supervised. In this paper, to take advantage of both limited labeled training images and rich unlabeled images, we propose a novel regularized Semi-Supervised Latent Dirichlet Allocation (r-SSLDA) for learning visual concept classifiers. Instead of introducing a new complex topic model, we attempt to find an efficient way to learn topic models in a semi-supervised way. Our r-SSLDA considers both semi-supervised properties and supervised topic model simultaneously in a regularization framework. Furthermore, to improve the performance of r-SSLDA, we introduce the low rank graph to the framework. Experiments on Caltech 101 and Caltech 256 have shown that r-SSLDA outperforms both unsupervised LDA and achieves competitive performance against fully supervised LDA with much fewer labeled images.