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Co-regularised support vector regression (2017)
Conference Proceeding
Ullrich, K., Kamp, M., Gärtner, T., Vogt, M., & Wrobel, S. (2017). Co-regularised support vector regression.

We consider a semi-supervised learning scenario for regression, where only few labelled examples, many unlabelled instances and different data representations (multiple views) are available. For this setting, we extend support vector regression with... Read More about Co-regularised support vector regression.

Nyström method with Kernel K-means++ samples as landmarks (2017)
Conference Proceeding
Oglic, D., & Gaertner, T. (2017). Nyström method with Kernel K-means++ samples as landmarks.

We investigate, theoretically and empirically, the effectiveness of kernel K-means++ samples as landmarks in the Nyström method for low-rank approximation of kernel matrices. Previous empirical studies (Zhang et al., 2008; Kumar et al.,2012) observe... Read More about Nyström method with Kernel K-means++ samples as landmarks.

Active search in intensionally specified structured spaces (2017)
Conference Proceeding
Oglic, D., Garnett, R., & Gärtner, T. (2017). Active search in intensionally specified structured spaces.

We consider an active search problem in intensionally specified structured spaces. The ultimate goal in this setting is to discover structures from structurally different partitions of a fixed but unknown target class. An example of such a process is... Read More about Active search in intensionally specified structured spaces.