In this study, a novel metaheuristic optimization algorithm, gradient-based optimizer (GBO) is proposed. The GBO, inspired by the gradient-based Newton's method, uses two main operators: gradient search rule (GSR) and local escaping operator (LEO) and a set of vectors to explore the search ...
逻辑超级简单,从buffer中拿一个LocalSyncParallelOptimizer出来,release是指要不要释放buffer里面这个optimizer(基于一些条件比如num_sgd_iter),之后呢就使用optimize方法更新一下权重,如果释放的话就把这个optimizer放到idle_optimizers中,最后再在outqueue中放一些信息进去就完了。 总结一下,多learner这种learner并行使用多个...
Adaptive particle swarm optimizerGradientImproving extremal optimizationMutation strategyMost real-world applications can be formulated as optimization problems, which commonly suffer from being trapped into the local optima. In this paper, we make full use of the global search capability of particle swarm...
A novel multi-objective improved gradient-based optimizer (MOIGBO) enhanced with Rosenbrock’s direct rotational technique to overcome premature convergence is proposed to determine the problem optimal decision variables. The deterministic optimization framework without uncertainty minimizes active energy loss,...
Firstly, we use the gradient based optimizer (GBO) in nonlinear inversion to obtain the source parameters of this seismic fault. The inversion results indicate that the strike of the fault is 206.52°, the dip is 44.10°, the length is 21.92 km, and the depth is 12.79 km. To refine the...
In addition to a highly-flexible optimization engine for general-purpose gradient-based optimization, Boulder Opal also features a gradient-free optimizer which can be directly applied to model-based control optimization for arbitrary-dimensional quantum systems. The gradient-free optimizer...
master BranchesTags Code README GPL-3.0 license GTOP:Gradient-Based Trajectory Optimizer (This repo is mainly developed and maintained byBoyu Zhou, please contace him if necessary) 1.Introduction Gradient-Based Online Safe Trajectory Generation is trajectory optimization framework, for generating a saf...
Firstly, we use the gradient based optimizer (GBO) in nonlinear inversion to obtain the source parameters of this seismic fault. The inversion results indicate that the strike of the fault is 206.52°, the dip is 44.10°, the length is 21.92 km, and the depth is 12.79 km. To refine the...
The optimizer, or better the numerical optimization algorithm, drives the optimization iterations. A parameter vector \(\textbf{x}\) describes the current state and is passed to the optimization processor. The optimization processor is the main interface for a numerical optimization algorithm and takes...
“Overcoming catastrophic forgetting in neural networks” by Kirkpatrick, P. et al., PNAS (2017). In one or more implementations, the fine-tuning module208optimizes the weights θ using a gradient-based optimizer, such as a number (e.g., 50) of optimization steps using an Adam optimizer....