Fast and simple gradient-based optimization for semi-supervised support vector machines
By Fabian Gieseke, Antti Airola, Tapio Pahikkala, Oliver Kramer. 2014
60 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Computer Vision and Pattern Recognition
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
- Marco Loog
- Alexander Mey
- Julius von Kügelgen
- Bernhard Schölkopf
- Dominik Janzing
- Arthur Gretton
- Kenji Fukumizu
- Jan Peters
In Computer Vision and Pattern Recognition
- Marco Loog
- Julius von Kügelgen
- Bernhard Schölkopf
- Alexander Mey
- Dacheng Tao
- Luc Van Gool
- Arthur Gretton
- Ming-Hsuan Yang
Citations in the corpus
- Semi-supervised learning, causality, and the conditional cluster assumption (2019, methodology): “We compare with T-SVMs [8, 16] with linear and RBF kernels using the q3svm implementation [26], and with label propagation [14, 15] using the implementation in sci-kit learn [27].”