On the exponential value of labeled samples
Pattern Recognition Letters
Nonlinear component analysis as a kernel eigenvalue problem
Neural Computation
Text Classification from Labeled and Unlabeled Documents using EM
Machine Learning - Special issue on information retrieval
Normalized Cuts and Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
Diffusion Kernels on Graphs and Other Discrete Input Spaces
ICML '02 Proceedings of the Nineteenth International Conference on Machine Learning
Learning from Labeled and Unlabeled Data using Graph Mincuts
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
Laplacian Eigenmaps for dimensionality reduction and data representation
Neural Computation
On clusterings-good, bad and spectral
FOCS '00 Proceedings of the 41st Annual Symposium on Foundations of Computer Science
The Journal of Machine Learning Research
Almost-everywhere algorithmic stability and generalization error
UAI'02 Proceedings of the Eighteenth conference on Uncertainty in artificial intelligence
Learning to cluster using local neighborhood structure
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Regularizing ad hoc retrieval scores
Proceedings of the 14th ACM international conference on Information and knowledge management
Semi-supervised learning with an imperfect supervisor
Knowledge and Information Systems
ICML '05 Proceedings of the 22nd international conference on Machine learning
Large margin non-linear embedding
ICML '05 Proceedings of the 22nd international conference on Machine learning
Higher order learning with graphs
ICML '06 Proceedings of the 23rd international conference on Machine learning
ICML '06 Proceedings of the 23rd international conference on Machine learning
Learning the unified kernel machines for classification
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Linear prediction models with graph regularization for web-page categorization
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
SmartLabel: an object labeling tool using iterated harmonic energy minimization
MULTIMEDIA '06 Proceedings of the 14th annual ACM international conference on Multimedia
A Framework for Learning Predictive Structures from Multiple Tasks and Unlabeled Data
The Journal of Machine Learning Research
Gaussian fields for semi-supervised regression and correspondence learning
Pattern Recognition
Manifold reconstruction in arbitrary dimensions using witness complexes
SCG '07 Proceedings of the twenty-third annual symposium on Computational geometry
Learning Coordinate Covariances via Gradients
The Journal of Machine Learning Research
Value Regularization and Fenchel Duality
The Journal of Machine Learning Research
Kernel selection forl semi-supervised kernel machines
Proceedings of the 24th international conference on Machine learning
Neighbor search with global geometry: a minimax message passing algorithm
Proceedings of the 24th international conference on Machine learning
Adaptive mesh compression in 3D computer graphics using multiscale manifold learning
Proceedings of the 24th international conference on Machine learning
Dimensionality reduction and generalization
Proceedings of the 24th international conference on Machine learning
Mining complex power networks for blackout prevention
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Semisupervised Regression with Cotraining-Style Algorithms
IEEE Transactions on Knowledge and Data Engineering
Nonsmooth Optimization Techniques for Semisupervised Classification
IEEE Transactions on Pattern Analysis and Machine Intelligence
Robust self-tuning semi-supervised learning
Neurocomputing
SVM-based active feedback in image retrieval using clustering and unlabeled data
Pattern Recognition
Covariate Shift Adaptation by Importance Weighted Cross Validation
The Journal of Machine Learning Research
Active Learning by Spherical Subdivision
The Journal of Machine Learning Research
Derivative reproducing properties for kernel methods in learning theory
Journal of Computational and Applied Mathematics
Graph Laplacian based transfer learning in reinforcement learning
Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 3
Analyzing Co-training Style Algorithms
ECML '07 Proceedings of the 18th European conference on Machine Learning
Regularization on Graphs with Function-adapted Diffusion Processes
The Journal of Machine Learning Research
Learning with sample dependent hypothesis spaces
Computers & Mathematics with Applications
Protein functional class prediction with a combined graph
Expert Systems with Applications: An International Journal
Incremental learning to rank with partially-labeled data
Proceedings of the 2009 workshop on Web Search Click Data
Error bounds of multi-graph regularized semi-supervised classification
Information Sciences: an International Journal
Semi-supervised document retrieval
Information Processing and Management: an International Journal
Semi-supervised Learning Based on Label Propagation through Submanifold
ISNN '09 Proceedings of the 6th International Symposium on Neural Networks on Advances in Neural Networks
Efficient Learning from Few Labeled Examples
ISNN '09 Proceedings of the 6th International Symposium on Neural Networks on Advances in Neural Networks
Learning Representation and Control in Markov Decision Processes: New Frontiers
Foundations and Trends® in Machine Learning
Learning representation and control in continuous Markov decision processes
AAAI'06 proceedings of the 21st national conference on Artificial intelligence - Volume 2
Weyl eigenvalue asymptotics and sharp adaptation on vector bundles
Journal of Multivariate Analysis
Discovering Process Models from Unlabelled Event Logs
BPM '09 Proceedings of the 7th International Conference on Business Process Management
Subspace Regularization: A New Semi-supervised Learning Method
ECML PKDD '09 Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part II
Samuel meets Amarel: automating value function approximation using global state space analysis
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 2
Clustering with local and global regularization
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
Semi-supervised learning with very few labeled training examples
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
Transductive Rademacher complexity and its applications
Journal of Artificial Intelligence Research
Ubiquitously supervised subspace learning
IEEE Transactions on Image Processing
Semi-automatically labeling objects in images
IEEE Transactions on Image Processing
Semi-supervised geodesic Generative Topographic Mapping
Pattern Recognition Letters
Traversable path identification in unstructured terrains: a Markov random walk approach
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Semisupervised multicategory classification with imperfect model
IEEE Transactions on Neural Networks
Distance approximating dimension reduction of Riemannian manifolds
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Interactive image segmentation using probabilistic hypergraphs
Pattern Recognition
A multilevel approach for learning from labeled and unlabeled data on graphs
Pattern Recognition
Transductive rademacher complexity and its applications
COLT'07 Proceedings of the 20th annual conference on Learning theory
Manifold learning-based feature transformation for phone classification
NOLISP'07 Proceedings of the 2007 international conference on Advances in nonlinear speech processing
A Modified Semi-Supervised Learning Algorithm on Laplacian Eigenmaps
Neural Processing Letters
Learning Gradients: Predictive Models that Infer Geometry and Statistical Dependence
The Journal of Machine Learning Research
Semi-supervised Bayesian ARTMAP
Applied Intelligence
Coresets and sketches for high dimensional subspace approximation problems
SODA '10 Proceedings of the twenty-first annual ACM-SIAM symposium on Discrete Algorithms
Learning shape segmentation using constrained spectral clustering and probabilistic label transfer
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part V
Artificial Intelligence in Medicine
Mixture graph based semi-supervised dimensionality reduction
Pattern Recognition and Image Analysis
Semi-supervised learning by spectral mapping with label information
AICI'10 Proceedings of the 2010 international conference on Artificial intelligence and computational intelligence: Part I
CIARP'10 Proceedings of the 15th Iberoamerican congress conference on Progress in pattern recognition, image analysis, computer vision, and applications
Manifold-respecting discriminant nonnegative matrix factorization
Pattern Recognition Letters
Nonparametric Regression between General Riemannian Manifolds
SIAM Journal on Imaging Sciences
Sparse regularization for semi-supervised classification
Pattern Recognition
Nonlinear discriminative embedding for clustering via spectral regularization
PAKDD'11 Proceedings of the 15th Pacific-Asia conference on Advances in knowledge discovery and data mining - Volume Part I
Local block representation for face recognition
ICSI'11 Proceedings of the Second international conference on Advances in swarm intelligence - Volume Part II
Horoball hulls and extents in positive definite space
WADS'11 Proceedings of the 12th international conference on Algorithms and data structures
Multiview semi-supervised learning for ranking multilingual documents
ECML PKDD'11 Proceedings of the 2011 European conference on Machine learning and knowledge discovery in databases - Volume Part III
Feature space warping relevance feedback with transductive learning
ACIVS'11 Proceedings of the 13th international conference on Advanced concepts for intelligent vision systems
Predicting clinical scores using semi-supervised multimodal relevance vector regression
MLMI'11 Proceedings of the Second international conference on Machine learning in medical imaging
A nonparametric classification method based on K-associated graphs
Information Sciences: an International Journal
Semi-supervised classification based on random subspace dimensionality reduction
Pattern Recognition
Mining Recurring Concept Drifts with Limited Labeled Streaming Data
ACM Transactions on Intelligent Systems and Technology (TIST)
One-Class support vector machines for recommendation tasks
PAKDD'06 Proceedings of the 10th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining
Combining smooth graphs with semi-supervised classification
PAKDD'06 Proceedings of the 10th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining
Uniform convergence of adaptive graph-based regularization
COLT'06 Proceedings of the 19th annual conference on Learning Theory
Mercer’s theorem, feature maps, and smoothing
COLT'06 Proceedings of the 19th annual conference on Learning Theory
On the relation of slow feature analysis and laplacian eigenmaps
Neural Computation
Learning bundle manifold by double neighborhood graphs
ACCV'09 Proceedings of the 9th Asian conference on Computer Vision - Volume Part III
Semi-supervised wavelet shrinkage
Computational Statistics & Data Analysis
Transductive segmentation of textured meshes
ACCV'09 Proceedings of the 9th Asian conference on Computer Vision - Volume Part II
Image classification by multimodal subspace learning
Pattern Recognition Letters
Keyword-propagation-based information enriching and noise removal for web news videos
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
Training pool selection for semi-supervised learning
ISNN'12 Proceedings of the 9th international conference on Advances in Neural Networks - Volume Part I
Proceedings of the 5th ACM workshop on Security and artificial intelligence
Information Sciences: an International Journal
Analysis of presence-only data via semi-supervised learning approaches
Computational Statistics & Data Analysis
CSS'12 Proceedings of the 4th international conference on Cyberspace Safety and Security
Learning colours from textures by sparse manifold embedding
Signal Processing
AusDM '08 Proceedings of the 7th Australasian Data Mining Conference - Volume 87
IScIDE'12 Proceedings of the third Sino-foreign-interchange conference on Intelligent Science and Intelligent Data Engineering
Document Re-ranking Using Partial Social Tagging
WI-IAT '12 Proceedings of the The 2012 IEEE/WIC/ACM International Joint Conferences on Web Intelligence and Intelligent Agent Technology - Volume 01
Semi-supervised learning with density-ratio estimation
Machine Learning
Intrinsic dimension identification via graph-theoretic methods
Journal of Multivariate Analysis
An introduction to artificial prediction markets for classification
The Journal of Machine Learning Research
A multi-manifold semi-supervised Gaussian mixture model for pattern classification
Pattern Recognition Letters
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We consider the general problem of utilizing both labeled and unlabeled data to improve classification accuracy. Under the assumption that the data lie on a submanifold in a high dimensional space, we develop an algorithmic framework to classify a partially labeled data set in a principled manner. The central idea of our approach is that classification functions are naturally defined only on the submanifold in question rather than the total ambient space. Using the Laplace-Beltrami operator one produces a basis (the Laplacian Eigenmaps) for a Hilbert space of square integrable functions on the submanifold. To recover such a basis, only unlabeled examples are required. Once such a basis is obtained, training can be performed using the labeled data set.Our algorithm models the manifold using the adjacency graph for the data and approximates the Laplace-Beltrami operator by the graph Laplacian. We provide details of the algorithm, its theoretical justification, and several practical applications for image, speech, and text classification.