"We then developed a quantum thermal gradient descent algorithm, which enables a quantum computer to efficiently find a local ...

Gradient descent searches for the function’s local minimum by looking for the direction of steepest ... There is a fundamental link between precision and speed in many complexity questions. For an ...

The last method is adjust(), which takes three arguments. These are values to apply to the weights and bias. It is important to notice that these arguments are subtracted. In gradient descent ...

It's a good spot from which to reflect on the mathematical tool called "stochastic gradient descent," a technique ... called spurious local minima, like a ridge along the way that only looks ...

In 1847, the French mathematician Augustin-Louis Cauchy was working on a suitably complicated example — astronomical calculations — when he pioneered a common method of optimization now known as ...

Progress in the online training of optical matrix computing chips has been made; compared to the discrete gradient descent algorithm, GA and PSO algorithm, this method greatly reduces the number ...