Support Vector Ordinal Regression
By Ralf Herbrich, Wei Chu, S. Sathiya Keerthi. Neural Computation, 2007
342 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Computer Vision and Pattern Recognition, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/de1729ca1d9dc951976f1f9fe2a08184207263a7
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- C. Hervás‐Martínez
- María Pérez-Ortiz
- Javier Sánchez-Monedero
- Francisco Fernández-Navarro
- Joe Naoum-Sawaya
- Pedro Antonio Gutiérrez
- Bissan Ghaddar
- Claudio Gambella
In Computer Vision and Pattern Recognition
- C. Hervás‐Martínez
- María Pérez-Ortiz
- Javier Sánchez-Monedero
- Francisco Fernández-Navarro
- Joe Naoum-Sawaya
- Pedro Antonio Gutiérrez
- Bissan Ghaddar
- Claudio Gambella
In Statistics and Probability
- C. Hervás‐Martínez
- María Pérez-Ortiz
- Javier Sánchez-Monedero
- Francisco Fernández-Navarro
- Joe Naoum-Sawaya
- Pedro Antonio Gutiérrez
- Bissan Ghaddar
- Claudio Gambella
Citations in the corpus
- Learning (predictive) risk scores in the presence of censoring due to interventions (2015, neutral): “In these cases, ordinal regression based approaches have been developed for ranking (Herbrich et al, 1999; Chu and Keerthi, 2007).”
- Ordinal Regression Methods: Survey and Experimental Study (2016, background): “…research [5]–[11], age estimation [12], brain computer interface [13], credit rating [14]–[17], econo-metric modelling [18], face recognition [19]–[21], facial beauty assessment [22], image classification [23], wind speed prediction [24], social sciences [25], text classification [26], and more.”
- Optimization Models for Machine Learning: A Survey (2019, background): “Following [68], the associated SVM formulation is”