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 ...
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 ...
High-performance matrix multiplication remains a cornerstone of numerical computing, underpinning a wide array of applications from scientific simulations to machine learning. Researchers continually ...
CHICAGO--(BUSINESS WIRE)--Matrix Executions, an agency-only broker dealer and trading technology provider, has enhanced its US listed options algorithm technology suite with new price discovery and ...
This is a preview. Log in through your library . Abstract The sparsity constrained rank-one matrix approximation problem is a difficult mathematical optimization problem which arises in a wide array ...
Mark Jerrum, Alistair Sinclair (UC Berkeley) and Eric Vigoda (Georgia Tech) received the Association for Computing Machinery (ACM) Test of Time Award at a virtual ceremony on Wednesday 23 June at the ...
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