learning algorithm

Multiple Attribute Information Decision Making Mode and Application Via Improved Fast Unsupervised Learning Algorithm

多属性信息决策的改进无监督学习算法建模与应用

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After carefully studying the assumption, loss function, optimization equation and learning algorithm, we conduct cross domain learning to rank at instance level and feature level.

在系统分析排序学习算法的基本假设、损失函数、优化公式和学习算法之后，本文分别在实例和特征两个方面进行迁移学习，给出各自的基本假设、优化公式以及学习算法。

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Learning Algorithm Selection in Meta-Learning and the Effect of Correlation

元学习算法选择机制及关联对性能的影响

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An Online Learning Algorithm of Support Vector Regression Based on Natural Gradient

基于自然梯度的支持向量回归在线算法

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It uses semi-supervised learning algorithm based on FCM, and for feature selection.

该方案使用的算法就是基于FCM的半监督学习算法，同时可以进行特征选择。

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An Unsupervised Learning Algorithm Based on Classification Weight and Mass Center Driving

基于分类权与质心驱动的无监督学习算法

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The self-organizing maps ( SOM) is an unsupervised learning algorithm, which is capable of self organization and visualization and has been used in many areas.

自组织映射（Self-Organizing Maps，SOM）算法是一种无导师学习方法，具有良好的自组织、可视化等特性，已经得到了广泛的应用和研究。

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A Study of EM Learning Algorithm Based on Gaussian Mixture Model

基于高斯混合模型的EM学习算法

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The paper presents an unsupervised learning algorithm to learn answer pattern for answer extraction module of Chinese Question Answering ( QA).

本文提出了一种基于无监督学习算法的问答模式抽取技术从互联网上抽取应用于汉语问答系统的答案模式。

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The methods of BSS and ICA are belong to a class of unsupervised learning algorithm, its algorithm theory and practical application are related the optimization of a number of areas of mathematics and neuroscience.

目前，ICA已经成为盲源分离的主流方法。BSS与ICA都属于一类无监督学习算法，他们的算法理论与实际应用涉及到优化数学和神经科学等多个领域。

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It is one kind of off-line learning algorithm, needs very few information about the object to control, therefore, it has very good control effects with some complex objects that difficulty modeling.

它是一种离线学习算法，需要很少的关于被控对象的信息，因此对于一些难以建模的复杂对象具有很好的控制效果。

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Thus, we propose a transfer learning algorithm for text classification based on clustering. This algorithm make use of cluster technology to find the instance that can help the learning of the new data from the auxiliary data.

提出一种基于聚类的文本迁移学习算法，利用聚类技术从原领域中寻找能够帮助目标数据学习的实例，用来帮助目标领域的学习。

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The Hamming-Graph Learning Algorithm of BNN

二进神经网络的汉明图学习算法

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This paper elaborates on the low learning efficiency in reinforcement learning due to improper generalization and random exploration policy under deterministic MDPS and proposes a hierarchical reinforcement learning algorithm based on system model.

针对强化学习算法的状态值泛化和随机探索策略在确定性MDP系统控制中存在着学习效率低的问题，本文提出基于模型的层次化强化学习算法。

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The ANN can derive a continuous-spread stability index to indicate the relative stability degree by means of a semi-supervised learning algorithm.

使用一个半监督学习算法，ANN可产生一个能够指示相对稳定度的连续分布的暂态稳定指标。

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BVM ( Ball Vector Machine) is a faster machine learning algorithm than SVM.

球向量机是一种比SVM更快的机器学习方法。

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A Semi-Supervised Learning Algorithm Based on Lie Group and Application

一种基于李群的半监督学习算法及应用研究

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Bayesian Network Classifier for Multi-spectral Image Based on K2 Structure Learning Algorithm

基于K2结构学习算法的多光谱影像贝叶斯网络分类器

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Classification accuracy of unsupervised learning algorithm is usually not satisfactory, so people tend to make use of supervised learning in practice.

由于无监督学习的准确率通常不能令人满意，在实际应用中人们趋向于运用有监督方法。

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This paper presents learning algorithm, points out the relation between layered attribute network and relational database, and realizes easy mutual action learning.

并给出了它的学习方法，方便实现互动式学习方式。

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A new hybrid learning algorithm was proposed to train the fuzzy neural network based on TSK fuzzy model. Firstly, fuzzy c-means algorithm was applied to initialize the parameters of the fuzzy neural network.

提出了一阶TSK模糊神经网络的混合学习算法，算法由三部分组成：基于模糊聚类的网络初始化；

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S(λ): A reinforcement learning algorithm based on average-payoff MDPs

S（λ）：一个基于平均奖赏MDPs的激励学习算法

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We can derive a self-organizing learning algorithm that maximizes the information transferred in a network of nonlinear units.

信息最大化方法将信息理论与神经网络相结合，根据使网络中所传递的信息量最大，推导出一种无监督学习准则。

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It is the key point of the support vector machine ensemble learning algorithm about how to work out much more effective ensemble learning algorithms.

如何设计出更有效的支持向量机集成学习实现算法，是目前支持向量机集成学习的关键问题。

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The paper first presents an objective model of task scheduling, and then based on the analysis of Q learning algorithm, the Markov decision process description of the scheduling problem is given.

首先建立任务调度问题的目标模型，在分析Q学习算法的基础上，给出调度问题的马尔可夫决策过程描述；

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The algorithm is based on Bayesian decision machinery, with estimation of the structure from probability density function, for two-class problems. ( 3) The paper gives out a semi-supervised learning algorithm based on FCM.

该算法基于贝叶斯决策理论，通过概率密度函数进行分布估计，对两类别半监督学习问题进行判定。（3）给出了一个基于FCM的半监督学习算法。

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As an important unsupervised learning algorithm without pre-marked samples in machine learning, clustering has been well developed in recent years.

聚类作为机器学习中一种重要的无监督学习算法，具有无需事前标记样本类型等优点，在近些年得到了很好地发展和应用。

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A transfer learning algorithm based on visual phrases is proposed.

第三，提出一种基于视觉短语的迁移学习算法。

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Considering discrete and successive state space separately, a entropy based reinforcement learning algorithm and an auto-generating neural network function approximator method for reinforcement learning are researched.

分别针对离散化的状态空间和连续状态空间的压缩问题，提出了基于信息熵的强化学习算法和基于自主生成神经网络函数逼近器的强化学习算法。

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Propose a semi-supervised learning algorithm based on ensemble learning.

提出了一种基于分类器集成的半监督学习算法。

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