Abstract: Graph convolutional networks (GCNs) are emerging neural network models designed to process graph-structured data. Due to massively parallel computations using irregular data structures by ...

Abstract: In this article, we investigate the optimal control problem for an unknown linear time-invariant system. To solve this problem, a novel composite policy iteration algorithm based on adaptive ...

This project investigates how different multithreaded matrix multiplication strategies affect performance. The objective was to implement parallel matrix multiplication to explore how thread count, ...