We describe a new approach for understanding the difficulty of designing efficient learning algorithms. We prove that the existence of an efficient learning algorithm for a circui...
This paper proposes a new connectionist approach to numeric law discovery; i.e., neural networks (law-candidates) are trained by using a newly invented second-order learning algor...
— Over time, neural networks have proven to be extremely powerful tools for data exploration with the capability to discover previously unknown dependencies and relationships in ...
PyBrain is a versatile machine learning library for Python. Its goal is to provide flexible, easyto-use yet still powerful algorithms for machine learning tasks, including a vari...
Tom Schaul, Justin Bayer, Daan Wierstra, Yi Sun, M...
Optimization of the control parameters of genetic algorithms is often a time consuming and tedious task. In this work we take the meta-level genetic algorithm approach to control ...