的目标函数 英语是什么意思 - 英语翻译

• objective function
• of the target function

在 中文 中使用 的目标函数 的示例及其翻译为 英语

于是式(7)的目标函数可表示为.
Then, the objective function(27) can be expressed as.

这样我们的目标函数就可以改写为.
So, our objective function can be rewritten as.

该图显示，两种方法都可以学习合理的目标函数模型。
The figure shows that both methods learn reasonable models of the target function.

深度学习模型的目标函数可能有若干局部最优值。
The objective function of the deep learning model may have several local optimums.

于是，我们的目标函数可以表示为：.
Therefore, our objective function can be represented as:.

在某些情况下，甚至难以定义明确的目标函数。
In some cases it can prove difficult to even define an explicit objective function.

这是我们线性回归的目标函数。
This was our objective function for the linear regression.

所以这将是我线性回归的整体目标函数。
So this is going to be my overall objective function for linear regression.

然后维持D不变，更新G的目标函数：.
Then maintain D unchanged and update the G's objective function:.

这种结构使得关于模型参数的目标函数更加稳定，帮助传播对于优化方法来说最重要的训练信号.
This makes the objective function more stable w. r. t. the model parameters, and helps propagate the training signal for first-order optimization methods.

典型设计优化技术的一个基本限制是它们需要单一的目标函数来评估性能。
A fundamental limitation of typical design optimization techniques is that they require a single objective function for evaluating performance.

该图显示，两种方法都可以学习到合理的目标函数模型。
The figure shows that both methods learn reasonable models of the target function.

线性规划(LP)涉及尽可能地减少或增加受边界、线性等式和不等式约束的目标函数。
Linear programming(LP), involves minimizing or maximizing a linear objective function subject to bounds, linear equality, and inequality constraints.

每个代理包含一个假设，该假设通过评估由代理的当前假设参数化的随机选择的部分目标函数来迭代测试。
Each agent maintains a hypothesis which is iteratively tested by evaluating a randomly selected partial objective function parameterised by the agent's current hypothesis.

事实上，几乎全部的目标函数和算法都有如此之高的Kolmogorov复杂性以至于它们不出现上述情况。
In practice, almost all objective functions and algorithms are of such high Kolmogorov complexity that they cannot arise.

许多机器学习任务涉及解决复杂的优化问题，例如处理不可微分，非连续和非唯一的目标函数;
Many machine learning tasks involve solving complex optimization problems, such as working on non-differentiable, non-continuous, and non-unique objective functions;

这三种情况引入了不同类型的目标函数和约束，并且可以适用于其他各种情况。
These three cases introduce different types of objective functions and constraints and can be adapted for a variety of other cases.

不幸的是，分隔三层的理论障碍在层次结构中告诉我们，我们的目标函数的性质并不重要。
Unfortunately, the theoretical barriers that separate the three layers in the hierarchy tell us that the nature of our objective function does not matter.

Hinton：Yann和Yoshua还认为--最大的困难并不是找到一个无监督学习的目标函数。
Hinton: Yann an Yoshua believe this as well- the biggest obstacle is not having an objective function of unsupervised learning.

研究者设计了“连续观测蒙特卡洛树搜索（continuous-observationMCTS）”，这种算法应用了高斯处理，以及一种新颖的目标函数来搜索这一片繁杂但存在可能路径的空间。
The researchers designed“continuous-observation MCTS,” which leverages the Gaussian process and the novel objective function to search over this unwieldy space of possible real paths.

在这种情况下，最小化的目标函数.
In these cases the objective function is reduced to.

最终，得出我们的目标函数（也称为代价函数）为：.
So the equation for the overall error(also called the cost function) will be:.

在简要地概述各种机器学习问题后，我们讨论线性回归，它的目标函数和闭合解。
After a brief overview of different machine learning problems, we discuss linear regression, its objective function and closed-form solution.

对于某些特定的问题，其具体的目标函数并没有先验知识，因此无法知道哪种代理模型最准确。
For some problems, the nature of true function is not known a priori so it is not clear which surrogate model will be most accurate.

我们设置函数的下限为目标函数:.
We put the sum of constraints as the objective function:.

此时，目标函数的值为.
The value of the objective function at this point is.

我们把要最小化或者最大化的函数称为目标函数或准则。
The function we want to minimize or maximize is called the objective function or criterion.

深度学习算法的目标函数，几乎全都是非凸的。
The target population for Learning Counts is almost incomprehensibly large.

目标函数的梯度使用Adjoint方法计算。
The gradient of the resulting objective function is calculated using the adjoint method.

在统计学中，拟合指的是你逼近目标函数的远近程度。
In statistics, a fit refers to how well you approximate a target function.