The learning algorithm maximizes the interclass margin and is referred to as the two stage margin maximization spiking neural network (TMM-SNN). In the structure learning stage, the learning algorithm ...

The traditional Newton algorithms for the problem require matrix multiplications and inversions, which are bottlenecks in modern Big Data contexts. A new Big Data-appropriate minorization-maximization ...

In this study, we propose a novel optimization algorithm for learning TN classifiers by using alternating least square (ALS) algorithm. Unlike conventional gradient-based methods, which suffer from ...

For example, in Circuit two Corners cannot be adjacent, yet they can be connected with a Connection tile, and diagonal tracks cannot change direction. WFC algorithm in higher dimensions works ...