Many robots are equipped with high-tech sensors and complex learning algorithms to avoid injuring humans as they work side by side.
许多机器人都配备了高科技传感器和复杂的学习算法，避免在与人类一起工作时伤害到人类。
The types of learning algorithms fall along several classifications.
学习算法分为几个不同的类别。
Genetic algorithms (GA) are optimization and machine learning algorithms inspired by processes of natural evolution.
遗传算法是由受生物进化过程启发而形成的进行优化和机器学习的算法。
Semi-supervised learning algorithms, which consider both labeled and unlabeled data, can improve learning effectiveness significantly.
半监督学习算法同时考虑有标记和无标记数据，能显著提升学习效果。
It is one of the most common learning algorithms in spam filters.
这是垃圾邮件过滤器中一种最常见的学习算法。
Document Indexing is a crucial step for learning algorithms and classifying systems.
文档索引对于学习算法和分类系统都是至关重要的一步。
Machine learning algorithms are being developed that allow robots and computers to learn autonomously.
机器学习算法正在被开发出来，它允许机器人和计算机进行自主学习。
Decision tree simplification is a significant branch in the study of decision-tree learning algorithms.
决策树简化是决策树学习算法中的一个重要分支。
Large scale machine learning problems always restrict real application of many ma-chine learning algorithms.
超大规模机器学习问题往往是许多机器学习算法在实际应用中的一大限制。
This paper gives a comprehensive overview about agent learning algorithms used in economic complexity system research.
对经济复杂性系统研究文献中常见的主体学习算法进行了一个全面的梳理。
At present, there are some hot topics in SVM researches, for example, model selection, fast learning algorithms et al.
目前SVM的研究热点主要有：svm的模型选择、快速学习算法研究等。
It supports directed and undirected models, discrete and continuous variables, various inference and learning algorithms.
它支持有向或无向的模型，离散或连续的变量，各种推论及学习算法。
The thesis mainly focuses on the dynamic scheduling method based on the averaged rewards reinforcement learning algorithms.
论文主要研究了基于平均型强化学习算法的动态调度方法。
The team rented Amazon's computers for less than a day to train machine-learning algorithms on more than 1.3 million files.
该团队租用亚马逊的计算机还不到一天，就对130多万个文件进行了机器学习算法的训练。
Designs of the iterative learning algorithms, the most important problems in the ILC, are also studied in this dissertation.
迭代学习算法设计一直是迭代学习控制研究的重点，本文从一些新的视角做了探讨。
The performance of these simple machine learning algorithms depends heavily on the representation of the data they are given.
这些简单的机器学习算法的性能很大程度上取决于他们所得到数据的表现形式（representation）。
It will use computer vision, sensors and deep learning algorithms to keep track of what customers are picking up off the shelves.
系统将会使用机械视觉、感应器和深度学习算法来跟踪记录顾客从货架上选取的商品。
It is rational to adopt the average reward reinforcement learning algorithms for solving the absorbing goal states cyclical tasks.
对于有吸收目标状态的循环任务，比较合理的方法是采用基于平均报酬模型的强化学习。
For example, you may write about the use of machine learning in natural language processing or review sample complexity of machine learning algorithms.
例如，你可以写关于在自然语言处理中使用机器学习的报告或机器学习中各算法的抽样复杂度的比较整理。
Fuzzy C-means clustering is one of the important learning algorithms in the field of pattern recognition, which has been applied early to image segmentation.
模糊c -均值聚类是模式识别中的重要算法之一，很早就被应用到图像分割中。
This paper presents two learning algorithms which can implement the ability of increasing knowledge in decision tree and the ability of learning from misjudgement.
本文详细地给出了决策树的两种学习算法，实现了决策树中知识的增长以及从误判中学习新的知识的功能。
SVM is a kind of general learning algorithms, which has been widely used in pattern recognition, regression estimation, function approximation, density estimation, etc.
支撑矢量机是一种普适的算法，已经广泛地用于模式识别、回归估计、函数逼近、密度估计等方面。
The continuous attribute problems are often encountered in the real world, but many outstanding inductive learning algorithms are mainly based on a discrete feature space.
实际问题中经常涉及连续的数值属性，然而许多归纳学习算法却是针对离散属性空间的。
To develop effective learning algorithms for fast and accurate continuous prediction using Electroencephalogram (EEG) signal is a key issue in BrainComputer Interface (BCI).
设计有效的学习算法快速准确地对脑电信号进行连续预测是脑机接口研究的关键之一。
This paper presents a class adaptive pole assignment control of servo systems based on neural state estimation and develops the system structure and the weight learning algorithms.
提出了一类基于神经元状态估计器的自适应广义极点配置控制，研究了该控制系统的网络结构和权值学习方法。
In order to extend common incremental learning algorithms into a parallel computation setting, an incremental learning algorithm with multiple support vector machine classifiers is proposed.
为了将一般增量学习算法扩展到并行计算环境中，提出一种基于多支持向量机分类器的增量学习算法。
The field goes by many names, such as connectionism, parallel distributed processing, neuro-computing, natural intelligent systems, machine learning algorithms, and artificial neural networks.
这个领域 有很多术语，例如连接机制、并行分布处理、神经计算、自然智能系统、机器学习算法和人工神经网络。
The field goes by many names, such as connectionism, parallel distributed processing, neuro-computing, natural intelligent systems, machine learning algorithms, and artificial neural networks.
这个领域 有很多术语，例如连接机制、并行分布处理、神经计算、自然智能系统、机器学习算法和人工神经网络。
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