A rigorous benchmark reveals that precision matrix estimation methods for transcriptomic co-expression networks vary ...

A machine learning study evaluating UCI breast tumor data demonstrated that the XGBoost model achieved 97.3 percent accuracy, ...

Can artificial intelligence (AI) create its own algorithms to speed up matrix multiplication, one of machine learning’s most fundamental tasks? Today, in a paper published in Nature, DeepMind unveiled ...

Researchers at MIT's Computer Science & Artificial Intelligence Lab (CSAIL) have open-sourced Multiply-ADDitioN-lESS (MADDNESS), an algorithm that speeds up machine learning using approximate matrix ...

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 ...

A new technique that efficiently retrieves scattered light from fluorescent sources can be used to record neuronal signals coming from deep within the brain. The technique, developed by physicists at ...

Fourier transforms are mathematical calculations that can be used to identify the frequencies that make up a signal and shed ...