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 paper, we propose a novel construction for secure distributed matrix multiplication (SDMM) based on algebraic geometry (AG) codes, which we call the PoleGap SDMM scheme. The proposed ...
CLA is a simple toy library for basic vector/matrix operations in C. This project main goal is to learn the foundations of CUDA, and Python bindings, using ctypes as a wrapper, through simple Linear ...
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