GitHub

microsoft/vptq

Vector Post-Training Quantization (VPTQ) is a novel Post-Training Quantization method that leverages Vector Quantization to high accuracy on LLMs at an extremely low bit-width (<2-bit). VPTQ can ...
IEEE

Over-the-Air Distributed Matrix-Vector Multiplication With Analog Coding

Abstract: Distributed matrix-vector multiplication plays a key role in numerous computing-intensive applications, including machine learning, by leveraging distributed computing resources known as ...
istockphoto

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Royalty-free licenses let you pay once to use copyrighted images and video clips in personal and commercial projects on an ongoing basis without requiring additional payments each time you use that ...
IEEE

Multi-User Sparse Vector Coding for eXtreme Ultra-Reliable Low-Latency Communication in Beyond 5G

Abstract: Short A short packet transmission scheme, such as Sparse Vector Coding (SVC), is a primary candidate for achieving ultra-low latency and high-reliability communication (URLLC). This paper ...