Efficient Sparse Matrix Encoding Via Low Subnormalization And Reduced Circuit Depth - Data Intelligence

Efficient Sparse Matrix Encoding Via Low Subnormalization And Reduced Circuit Depth - Data Intelligence

Efficient Sparse Matrix Encoding via Low Subnormalization and Reduced Circuit Depth Introduction Sparse matrices are omnipresent in computational fields such as scientific computing, machine learning, and graph theory. They are characterized by a significant number of zero elements, which makes traditional matrix storage and computation inefficient. Hence, innovative techniques for efficient encoding and processing of sparse matrices are critica…