  The main goal of this work is to improve the efficiency of training binary
neural networks, which are low latency and low energy networks. The main
contribution of this work is the proposal of two solutions comprised of
topology changes and strategy training that allow the network to achieve near
the state-of-the-art performance and efficient training. The time required for
training and the memory required in the process are two factors that contribute
to efficient training.

Machine Learning;Artificial Intelligence;Neural and Evolutionary Computing