With the goal to generate more scalable algorithms with higher efficiency and fewer open parameters, reinforcement learning (RL) has recently moved towards combining classical tec...
Efficient energy and performance estimation of embedded software is a critical part of any system-level design flow. Macromodeling based estimation is an attempt to speed up estim...
The paper introduces a new framework for feature learning in classification motivated by information theory. We first systematically study the information structure and present a n...