Background: Diverse modeling approaches viz. neural networks and multiple regression have been followed to date for disease prediction in plant populations. However, due to their ...
Rakesh Kaundal, Amar S. Kapoor, Gajendra P. S. Rag...
The complexity of the kinematic and dynamic structure of humanoid robots make conventional analytical approaches to control increasingly unsuitable for such systems. Learning techn...
We consider the problem of numerical stability and model density growth when training a sparse linear model from massive data. We focus on scalable algorithms that optimize certain...
Abstract. We present an implementation of model-based online reinforcement learning (RL) for continuous domains with deterministic transitions that is specifically designed to achi...
Without rigorous software development and maintenance, software tends to lose its original architectural structure and become difficult to understand and modify. ArchJava, a recen...
Marwan Abi-Antoun, Jonathan Aldrich, Wesley Coelho