This paper introduces a simple yete ective method for using causal domain knowledge for learning to control dynamic systems. Elementary qualitative causal dependencies of the domai...
— In recent years, learning models from data has become an increasingly interesting tool for robotics, as it allows straightforward and accurate model approximation. However, in ...
We introduce novel discriminative learning algorithms for dynamical systems. Models such as Conditional Random Fields or Maximum Entropy Markov Models outperform the generative Hi...
Learning in real-time applications, e.g., online approximation of the inverse dynamics model for model-based robot control, requires fast online regression techniques. Inspired by...
The intensive care unit is a challenging environment to both patient and caregiver. Continued shortages in staffing, principally in nursing, increase risk to patient and healthcar...
Brett L. Moore, Eric D. Sinzinger, Todd M. Quasny,...