Application of active learning for support vector machines

The active learning approach enables application of support vector machines and other machine learning techniques on big data sets. One of the benefits is also the reduction of model size. I have published two papers in a respectable journal about this topic and I am awaiting review for one more journal paper.

  • V. Ceperic, G. Gielen, and A. Baric. “Recurrent sparse support vector regression machines trained by active learning in the time-domain”. In: Expert Systems with Applications 39.12 (2012), pp. 10933—10942. Corresponding author.
  • V. Ceperic, G. Gielen, and A. Baric. “Sparse multikernel support vector regression machines trained by active learning”. In: Expert Systems with Applications 39.12 (2012), pp. 11029—11035. Corresponding author.