Normalized Cuts and Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Transductive Inference for Text Classification using Support Vector Machines
ICML '99 Proceedings of the Sixteenth International Conference on Machine Learning
Laplacian Eigenmaps for dimensionality reduction and data representation
Neural Computation
Semi-supervised protein classification using cluster kernels
Bioinformatics
Spectral Methods for Automatic Multiscale Data Clustering
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
Unsupervised learning of image manifolds by semidefinite programming
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Video suggestion and discovery for youtube: taking random walks through the view graph
Proceedings of the 17th international conference on World Wide Web
Weakly-supervised acquisition of labeled class instances using graph random walks
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Ranking and semi-supervised classification on large scale graphs using map-reduce
TextGraphs-4 Proceedings of the 2009 Workshop on Graph-based Methods for Natural Language Processing
COSNet: a cost sensitive neural network for semi-supervised learning in graphs
ECML PKDD'11 Proceedings of the 2011 European conference on Machine learning and knowledge discovery in databases - Volume Part I
MapReduce approach to collective classification for networks
ICAISC'12 Proceedings of the 11th international conference on Artificial Intelligence and Soft Computing - Volume Part I
Hypergraph learning with hyperedge expansion
ECML PKDD'12 Proceedings of the 2012 European conference on Machine Learning and Knowledge Discovery in Databases - Volume Part I
International Journal of Intelligent Systems Technologies and Applications
Relational large scale multi-label classification method for video categorization
Multimedia Tools and Applications
Semi-supervised learning using greedy max-cut
The Journal of Machine Learning Research
Semi-supervised clustering via multi-level random walk
Pattern Recognition
A few good predictions: selective node labeling in a social network
Proceedings of the 7th ACM international conference on Web search and data mining
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We consider the problem of multiclass classification where both labeled and unlabeled data points are given. We introduce and demonstrate a new approach for estimating a distribution over the missing labels where data points are viewed as nodes of a graph, and pairwise similarities are used to derive a transition probability matrix P for a Markov random walk between them. The algorithm associates each point with a particle which moves between points according to P. Labeled points are set to be absorbing states of the Markov random walk, and the probability of each particle to be absorbed by the different labeled points, as the number of steps increases, is then used to derive a distribution over the associated missing label. A computationally efficient algorithm to implement this is derived and demonstrated on both real and artificial data sets, including a numerical comparison with other methods.