Sentence examples for estimating the gradient of from inspiring English sources

A discrete-time sliding mode gradient estimator is developed for estimating the gradient of the performance profile.

Also, in this second output coding paradigm, the bCR-update is found to be much more efficient in estimating the gradient of the expected reward.

Here this property is utilized for estimating the gradient of an optimal control type cost function with respect to the design parameters of the controllers.

The results, however, show that compared to ZR the bCR rule provides a less noisy procedure for estimating the gradient of the log-likelihood of the somatic response given the neuronal input ( ∂ ∂ w i, ν log P w ( Z | X ) ). Estimating this gradient for each neuron is also the key step for reinforcement learning in networks of complex cells [13].

Our method works by estimating the gradient of the likelihood function first, and then searching for an optimal solution by iteratively updating the parameters along the gradient descent direction.

Instead of calculating and approximating the likelihood function as in the previous methods, we focus on estimating the gradients of the likelihood function with respect to the parameters.

An Artificial Neural Network is employed as a Critic to estimate the gradient of cost-to-go function.

We assume that the agents can estimate the gradient of the cost function element-wise by measuring the steady state response of the system.

Respect to other optimization methods, the optimization techniques based on gradient attempt to estimate the gradient of the error surface and proceed to an optimum solution by following the negative direction of this estimated vector.

At each step of the gradient descent, we had to sample a set of sequences by Gibbs sampling, under the current values of the parameters, so as to numerically estimate the gradient of the log-likelihood.

Our algorithm estimates the gradient of the likelihood function by reversible jump Markov chain Monte Carlo sampling (RJMCMC), and then gradient descent method is employed to obtain the maximum likelihood estimation of parameter values.