Eligibility traces have been shown to speed reinforcement learning, to make it more robust to hidden states, and to provide a link between Monte Carlo and temporal-difference meth...
Doina Precup, Richard S. Sutton, Satinder P. Singh
The present paper motivates the study of mind change complexity for learning minimal models of length-bounded logic programs. It establishes ordinal mind change complexity bounds ...
It is well known that many hard tasks considered in machine learning and data mining can be solved in a rather simple and robust way with an instanceand distance-based approach. In...
Constructing a high-resolution (HR) image from lowresolution (LR) image(s) has been a very active research topic recently with focus shifting from multi-frames to learning based s...
This contribution develops a theoretical framework that takes into account the effect of approximate optimization on learning algorithms. The analysis shows distinct tradeoffs for...