Abstract: We study the complexity of simulating a neural network. We simplified the model of a neural network as a directed graph $G(V,E)$, where the nodes represent the neurons.

Abstract: Multiobjective Optimization Problems (MOPs) characterize an essential class of optimization problems that involve optimizing more than one objective function simultaneously.

Abstract: We are in the midst of a major data revolution. The total data generated by humans from the dawn of civilization until the turn of the new millennium is now being generated every other day.

Abstract: The probabilistic degree of a Boolean function f is defined to be the smallest d such that there is a random polynomial P of degree at most d that agrees with f at each point with high probability.