High-performance matrix multiplication remains a cornerstone of numerical computing, underpinning a wide array of applications from scientific simulations to machine learning. Researchers continually ...
A new research paper titled “Discovering faster matrix multiplication algorithms with reinforcement learning” was published by researchers at DeepMind. “Here we report a deep reinforcement learning ...
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RRAM-based analog computing system rapidly solves matrix equations with high precision
Analog computers are systems that perform computations by manipulating physical quantities such as electrical current, that ...
A Hong Kong-based Matrix AI Network is developing a prototype of a new hybrid PoS/PoW consensus algorithm. This update was shared with Cointelegraph by Owen Tao, the company’s CEO. Tao described ...
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 ...
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 difficult tasks in numerical ...
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