Transductive Inference for Text Classification using Support Vector Machines
ICML '99 Proceedings of the Sixteenth International Conference on Machine Learning
Kernel conditional random fields: representation and clique selection
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Support vector machine learning for interdependent and structured output spaces
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Beyond the point cloud: from transductive to semi-supervised learning
ICML '05 Proceedings of the 22nd international conference on Machine learning
Semi-supervised learning for structured output variables
ICML '06 Proceedings of the 23rd international conference on Machine learning
Discriminative unsupervised learning of structured predictors
ICML '06 Proceedings of the 23rd international conference on Machine learning
Training a Support Vector Machine in the Primal
Neural Computation
Transductive multi-label learning for video concept detection
MIR '08 Proceedings of the 1st ACM international conference on Multimedia information retrieval
Learning structural SVMs with latent variables
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
Active and Semi-supervised Data Domain Description
ECML PKDD '09 Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part I
Active learning for network intrusion detection
Proceedings of the 2nd ACM workshop on Security and artificial intelligence
A novel approach for distributed application scheduling based on prediction of communication events
Future Generation Computer Systems
A transductive multi-label learning approach for video concept detection
Pattern Recognition
Learning from partially annotated sequences
ECML PKDD'11 Proceedings of the 2011 European conference on Machine learning and knowledge discovery in databases - Volume Part I
Structured Output SVM for Remote Sensing Image Classification
Journal of Signal Processing Systems
Multi-view prediction of protein function
Proceedings of the 2nd ACM Conference on Bioinformatics, Computational Biology and Biomedicine
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part VII
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We study the problem of learning kernel machines transductively for structured output variables. Transductive learning can be reduced to combinatorial optimization problems over all possible labelings of the unlabeled data. In order to scale transductive learning to structured variables, we transform the corresponding non-convex, combinatorial, constrained optimization problems into continuous, unconstrained optimization problems. The discrete optimization parameters are eliminated and the resulting differentiable problems can be optimized efficiently. We study the effectiveness of the generalized TSVM on multiclass classification and label-sequence learning problems empirically.