Kazuki Iwamura

  • Citations Per Year
Learn More
We discuss sparse support vector machines (sparse SVMs) trained in the reduced empirical feature space. Namely, we select the linearly independent training data by the Cholesky factorization of the kernel matrix, and train the SVM in the dual form in the reduced empirical feature space. Since the mapped linearly independent training data span the empirical(More)
This paper deals with a real-time scheduling system of holonic manufacturing systems (HMSs), which were proposed by an international cooperative research consortium called The HMS Consortium for Autonomous Distributed Management and Control of the Manufacturing Systems. The scheduling system generates real-time suitable production schedules, based on(More)
  • 1