Abstract: Approximation ability is one of the most important topics in the field of neural networks (NNs). Feedforward NNs, activated by rectified linear units and some of their specific smoothed ...

O n Tuesday, researchers at Stanford and Yale revealed something that AI companies would prefer to keep hidden. Four popular ...

Research team debuts the first deterministic streaming algorithms for non-monotone submodular maximization, delivering superior approximation ratios with minimal memory and real-time throughput on ...

Abstract: Training a one-node neural network with the ReLU activation function via optimization, which we refer to as the ON-ReLU problem, is a fundamental problem in machine learning. In this paper, ...

ABSTRACT: In this paper, we introduce a method to obtain the nearest trapezoidal approximation of fuzzy numbers so that preserving conditions expect interval and include the core of a fuzzy number.