Bayesian Gaussian Process Classification with the EM-EP Algorithm
IEEE Transactions on Pattern Analysis and Machine Intelligence
Assessing Approximate Inference for Binary Gaussian Process Classification
The Journal of Machine Learning Research
ROC analysis in ordinal regression learning
Pattern Recognition Letters
SoftRank: optimizing non-smooth rank metrics
WSDM '08 Proceedings of the 2008 International Conference on Web Search and Data Mining
The unimodal model for the classification of ordinal data
Neural Networks
On the scalability of ordered multi-class ROC analysis
Computational Statistics & Data Analysis
Learning diverse rankings with multi-armed bandits
Proceedings of the 25th international conference on Machine learning
A New Probabilistic Approach in Rank Regression with Optimal Bayesian Partitioning
The Journal of Machine Learning Research
Learning to rank with SoftRank and Gaussian processes
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Improving maximum margin matrix factorization
Machine Learning
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
Generalization Bounds for Some Ordinal Regression Algorithms
ALT '08 Proceedings of the 19th international conference on Algorithmic Learning Theory
Knowledge and Information Systems
Bagging for Gaussian process regression
Neurocomputing
Matchbox: large scale online bayesian recommendations
Proceedings of the 18th international conference on World wide web
Classification of Protein Interaction Sentences via Gaussian Processes
PRIB '09 Proceedings of the 4th IAPR International Conference on Pattern Recognition in Bioinformatics
Adding redundant features for CRFs-based sentence sentiment classification
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Learning Preferences with Hidden Common Cause Relations
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
Block-quantized support vector ordinal regression
IEEE Transactions on Neural Networks
Preference learning with extreme examples
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Cost-sensitive supported vector learning to rank imbalanced data set
ICIC'09 Proceedings of the Intelligent computing 5th international conference on Emerging intelligent computing technology and applications
Ordinal regression with sparse Bayesian
ICIC'09 Proceedings of the Intelligent computing 5th international conference on Emerging intelligent computing technology and applications
Semi-parametric analysis of multi-rater data
Statistics and Computing
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
Ordinal extreme learning machine
Neurocomputing
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
Protein interaction detection in sentences via Gaussian Processes: a preliminary evaluation
International Journal of Data Mining and Bioinformatics
Learning Transformation Models for Ranking and Survival Analysis
The Journal of Machine Learning Research
OrdRec: an ordinal model for predicting personalized item rating distributions
Proceedings of the fifth ACM conference on Recommender systems
Modeling personalized email prioritization: classification-based and regression-based approaches
Proceedings of the 20th ACM international conference on Information and knowledge management
A hierarchical model for ordinal matrix factorization
Statistics and Computing
An experimental study of different ordinal regression methods and measures
HAIS'12 Proceedings of the 7th international conference on Hybrid Artificial Intelligent Systems - Volume Part II
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
HAIS'12 Proceedings of the 7th international conference on Hybrid Artificial Intelligent Systems - Volume Part II
A weakly supervised model for sentence-level semantic orientation analysis with multiple experts
EMNLP-CoNLL '12 Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning
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
Shame to be sham: addressing content-based grey hat search engine optimization
Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval
Ranked bandits in metric spaces: learning diverse rankings over large document collections
The Journal of Machine Learning Research
Retargeted matrix factorization for collaborative filtering
Proceedings of the 7th ACM conference on Recommender systems
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
Kernelizing the proportional odds model through the empirical kernel mapping
IWANN'13 Proceedings of the 12th international conference on Artificial Neural Networks: advances in computational intelligence - Volume Part I
An n-spheres based synthetic data generator for supervised classification
IWANN'13 Proceedings of the 12th international conference on Artificial Neural Networks: advances in computational intelligence - Volume Part I
Conditional ordinal random fields for structured ordinal-valued label prediction
Data Mining and Knowledge Discovery
Robust ordinal regression in preference learning and ranking
Machine Learning
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We present a probabilistic kernel approach to ordinal regression based on Gaussian processes. A threshold model that generalizes the probit function is used as the likelihood function for ordinal variables. Two inference techniques, based on the Laplace approximation and the expectation propagation algorithm respectively, are derived for hyperparameter learning and model selection. We compare these two Gaussian process approaches with a previous ordinal regression method based on support vector machines on some benchmark and real-world data sets, including applications of ordinal regression to collaborative filtering and gene expression analysis. Experimental results on these data sets verify the usefulness of our approach.