We present and analyze a novel regularization technique based on enhancing our dataset with corrupted copies of our original data. The motivation is that since the learning algori...
Abstract. A conceptual framework, whose goal is the improvement of efficiency of machine learning, is presented. The framework is designed in a broader context of problem solver (P...
This paper describes the efforts undertaken in an international research project LT4eL from the perspective of one of the participating languages, Czech. The project aims at explo...
This paper presents the application of a reinforcement learning (RL) approach for the near-optimal control of a re-entrant line manufacturing (RLM) model. The RL approach utilizes...
We view dynamic scheduling as a sequential decision problem. Firstly, we introduce a generalized planning operator, the stochastic task model (STM), which predicts the effects of ...