The nature of statistical learning theory
The nature of statistical learning theory
Fast training of support vector machines using sequential minimal optimization
Advances in kernel methods
Improvements to Platt's SMO Algorithm for SVM Classifier Design
Neural Computation
Prediction of Ordinal Classes Using Regression Trees
Fundamenta Informaticae - Intelligent Systems
Adapting ranking SVM to document retrieval
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Focused crawling with scalable ordinal regression solvers
Proceedings of the 24th international conference on Machine learning
Magnitude-preserving ranking algorithms
Proceedings of the 24th international conference on Machine learning
Ranking with multiple hyperplanes
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
ROC analysis in ordinal regression learning
Pattern Recognition Letters
The unimodal model for the classification of ordinal data
Neural Networks
On the scalability of ordered multi-class ROC analysis
Computational Statistics & Data Analysis
A New Probabilistic Approach in Rank Regression with Optimal Bayesian Partitioning
The Journal of Machine Learning Research
Learning to Predict One or More Ranks in Ordinal Regression Tasks
ECML PKDD '08 Proceedings of the 2008 European Conference on Machine Learning and Knowledge Discovery in Databases - Part I
Adding monotonicity to learning algorithms may impair their accuracy
Expert Systems with Applications: An International Journal
Two algorithms for generating structured and unstructured monotone ordinal data sets
Engineering Applications of Artificial Intelligence
Minimally invasive randomization for collecting unbiased preferences from clickthrough logs
AAAI'06 proceedings of the 21st national conference on Artificial intelligence - Volume 2
Binary Decomposition Methods for Multipartite Ranking
ECML PKDD '09 Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part I
Learning to Rank for Information Retrieval
Foundations and Trends in Information Retrieval
Kernel regression with order preferences
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
Prediction and change detection in sequential data for interactive applications
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 2
Ranking structured documents: a large margin based approach for patent prior art search
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
MINLIP: Efficient Learning of Transformation Models
ICANN '09 Proceedings of the 19th International Conference on Artificial Neural Networks: Part I
Cascade generalisation for ordinal problems
International Journal of Artificial Intelligence and Soft Computing
An alternative ranking problem for search engines
WEA'07 Proceedings of the 6th international conference on Experimental algorithms
Ordinal classification with decision rules
MCD'07 Proceedings of the 3rd ECML/PKDD international conference on Mining complex data
Ordinal regression with sparse Bayesian
ICIC'09 Proceedings of the Intelligent computing 5th international conference on Emerging intelligent computing technology and applications
Large margin cost-sensitive learning of conditional random fields
Pattern Recognition
Capturing the stars: predicting ratings for service and product reviews
SS '10 Proceedings of the NAACL HLT 2010 Workshop on Semantic Search
How about utilizing ordinal information from the distribution of unlabeled data
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
PAGER: parameterless, accurate, generic, efficient kNN-based regression
DEXA'10 Proceedings of the 21st international conference on Database and expert systems applications: Part II
Hidden conditional ordinal random fields for sequence classification
ECML PKDD'10 Proceedings of the 2010 European conference on Machine learning and knowledge discovery in databases: Part II
ICANN'10 Proceedings of the 20th international conference on Artificial neural networks: Part II
Adapting decision DAGs for multipartite ranking
ECML PKDD'10 Proceedings of the 2010 European conference on Machine learning and knowledge discovery in databases: Part III
Structured output ordinal regression for dynamic facial emotion intensity prediction
ECCV'10 Proceedings of the 11th European conference on computer vision conference on Computer vision: Part III
Ordinal-class core vector machine
Journal of Computer Science and Technology
Exploiting separability in large-scale linear support vector machine training
Computational Optimization and Applications
Post-ranking query suggestion by diversifying search results
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
Learning Transformation Models for Ranking and Survival Analysis
The Journal of Machine Learning Research
Modeling personalized email prioritization: classification-based and regression-based approaches
Proceedings of the 20th ACM international conference on Information and knowledge management
Large-Margin thresholded ensembles for ordinal regression: theory and practice
ALT'06 Proceedings of the 17th international conference on Algorithmic Learning Theory
Cost-Sensitive learning of SVM for ranking
ECML'06 Proceedings of the 17th European conference on Machine Learning
The discovery and use of ordinal information on attribute values in classifier learning
AI'11 Proceedings of the 24th international conference on Advances in Artificial Intelligence
Neural network ensembles to determine growth multi-classes in predictive microbiology
HAIS'12 Proceedings of the 7th international conference on Hybrid Artificial Intelligent Systems - Volume Part II
BINER: BINary search based efficient regression
MLDM'12 Proceedings of the 8th international conference on Machine Learning and Data Mining in Pattern Recognition
Neighborhood preserving ordinal regression
Proceedings of the 4th International Conference on Internet Multimedia Computing and Service
The classification of cancer stage microarray data
Computer Methods and Programs in Biomedicine
Evolutionary extreme learning machine for ordinal regression
ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part III
Validation based sparse gaussian processes for ordinal regression
ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part II
Statistical models and learning algorithms for ordinal regression problems
Information Fusion
A probabilistic least squares approach to ordinal regression
AI'12 Proceedings of the 25th Australasian joint conference on Advances in Artificial Intelligence
Probabilistic generative ranking method based on multi-support vector domain description
Information Sciences: an International Journal
Exploitation of pairwise class distances for ordinal classification
Neural Computation
Conditional ordinal random fields for structured ordinal-valued label prediction
Data Mining and Knowledge Discovery
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In this paper, we propose two new support vector approaches for ordinal regression, which optimize multiple thresholds to define parallel discriminant hyperplanes for the ordinal scales. Both approaches guarantee that the thresholds are properly ordered at the optimal solution. The size of these optimization problems is linear in the number of training samples. The SMO algorithm is adapted for the resulting optimization problems; it is extremely easy to implement and scales efficiently as a quadratic function of the number of examples. The results of numerical experiments on benchmark datasets verify the usefulness of these approaches.