“We must strive for better,” said IBM Research chief scientist Ruchir Puri at a conference on AI acceleration organised by the computer company and the IEEE in November. He expects almost all language ...
Abstract: Sparse matrix-vector multiplication (SpMV) is a fundamental operation in machine learning, scientific computing, and graph algorithms. In this paper, we investigate the space, time, and ...
An Ensemble Learning Tool for Land Use Land Cover Classification Using Google Alpha Earth Foundations Satellite Embeddings ...
MicroCloud Hologram Inc. (NASDAQ: HOLO), (“HOLO” or the “Company”), a technology service provider, released learnable quantum spectral filter technology for hybrid graph neural networks. This ...
CNBC's Squawk Box Asia Martin Soong and Chery Kang talk about AMD's chip supply deal with OpenAI, plus the web of alliances, cross shareholdings and the money loop that could shape the AI space. Major ...
Hey there! I'm Aayush Khanna from Noida, Uttar Pradesh, India. I am a third year undergrad pursuing civil engineering at the Indian institute of Technology (BHU), Varanasi. I am interested in all ...
Presented about our project and the progress to our project advisors. Concatenated all inputs into one input in HLS; to have less wiring. Worked on an error in HLS ...
Imagine giving a familiar medication a whole new purpose—finding fresh treatments without starting from scratch. That’s precisely what a team of researchers at Xidian University in China has been ...
Dozens of machine learning algorithms require computing the inverse of a matrix. Computing a matrix inverse is conceptually easy, but implementation is one of the most challenging tasks in numerical ...
Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of computing a matrix inverse using the Newton iteration algorithm. Compared to other algorithms, Newton ...
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