Machine learning for quantum physics.
Originally shared by Wayne Radinsky
Machine learning for quantum physics. "Researchers have introduced an approach to quantum machine learning that unifies much of the prior work and extends it to problems that received little attention before."
"The new work provides a Rosetta Stone that translates the language of reinforcement learning to the quantum realm. It tackles sticky questions like what it means for a quantum agent to learn and how the history of a quantum agent's interaction with its environment can be captured in a meaningful way. It also shows how a standard algorithm in the quantum toolkit can help agents learn faster in settings where an early stroke of luck can make a big difference."
http://jqi.umd.edu/news/quantum-bit/2016/09/15/machine-learning-quantum-world
Machine learning for quantum physics. "Researchers have introduced an approach to quantum machine learning that unifies much of the prior work and extends it to problems that received little attention before."
"The new work provides a Rosetta Stone that translates the language of reinforcement learning to the quantum realm. It tackles sticky questions like what it means for a quantum agent to learn and how the history of a quantum agent's interaction with its environment can be captured in a meaningful way. It also shows how a standard algorithm in the quantum toolkit can help agents learn faster in settings where an early stroke of luck can make a big difference."
http://jqi.umd.edu/news/quantum-bit/2016/09/15/machine-learning-quantum-world
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