迁移学习

基于迁移学习的自适应室内Wi-Fi定位

Adaptive Localization in Indoor Wi-Fi Environment Based on Transfer Learning

第三，提出一种基于视觉短语的迁移学习算法。

A transfer learning algorithm based on visual phrases is proposed .

TTL和传统的基于迁移学习的协同过滤推荐系统相比有一些新的特征。

TTL has some novel features over traditional collaborative filtering on cross domain .

这两种算法分别对应基于实例的迁移学习和基于特征的迁移学习。

These two algorithms corresponds to instance-based and feature-based transfer learning .

迁移学习能够有效解决这个问题。

Transfer learning can effectively solve this problem .

因此，迁移学习不会像传统机器学习那样作同分布假设。

Thus , transfer learning does not make the identical-distribution assumption as tractional machine learning algorithms .

基于实例和特征的迁移学习算法研究

Instance-based and Feature-based Transfer Learning

我们的工作可以分为两部分；基于实例的迁移学习和基于特征的迁移学习。

Our work can be divided into two parts : instance-based transfer learn-ing , and feature-based transfer learning .

一种面向非线性回归的迁移学习模型

Non-linear Transfer Learning Model

迁移学习能够将以往学到的知识迁移到新任务的学习中，帮助新任务的学习。

Transfer learning can transfer previously knowledge to a new task , helping the learning of a new task .

本文主要研究了在文本分类过程中，如何同时利用新数据与旧数据，进行特征提取，才能够更好的适应迁移学习算法，使得文本分类获得更好的效果。

Paper also researches how to simultaneously use the old data with new data , to achieve better classification results .

该交叉域的迁移学习的方法可以通过未标注真实类别标签的网络多媒体数据完成有监督分类的学习任务。

Our proposed cross-domain transfer learning method for utilizing web multimedia objects without true labels in performing supervised classification tasks .

该模型主要包括两个部分：基于流形学习的样本筛选方法和基于迁移学习的分类器设计。

The model consists of two parts : sample screening method based manifold learning and classification model design based transfer learning .

另外，分类器设计采用迁移学习的思想，通过专门设计调整权重策略来更新样本的权重。

In addition , the classifier designs with the idea of transfer learning and adjusts the sample weight through special strategies .

已有研究者使用多模态学习、多任务学习和迁移学习等方法，将图像相关的文本信息引入图像分类任务中，实验表明引入与图像相关的文本信息对图像分类性能有所提升。

Researchers have employed multi-modal learning , multi-task learning and transfer learning methods to bring the image associated text information into image classification tasks .

作为机器学习领域中最重要的研究方向之一，迁移学习在近几年来开始得到了越来越多的关注。

Serving as one of the most important research directions in machine learning , transfer learning has begun to catch more attention in recent years .

迁移学习的研究出于这样一个指导信息：人类可以利用先前所学到的知识来更好更快地解决新的问题。

The study of Transfer learning is motivated by the fact that people can intelligently apply knowledge learned previously to solve new problems faster or with better solutions .

最后，以词汇语义相似度方法获取各个领域的问句特征空间特征值。2、在中文问句领域分类移植方面，提出了一种基于特征映射的问句分类迁移学习方法。

Finally , get the feature value of different question domains with the word semantic similarity method.2.This paper proposed a question classification method based on feature mapping transfer learning .

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。

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 .

本文通过迁移学习的方法，利用从源领域中学习到的知识帮助并加快目标领域的学习，并在此基础上实现了一种基于归纳式迁移学习的商品图像分类算法。

This paper use the knowledge learnt from the source domain to help and speed up learning in the target domain through transfer learning , and implement a product image classification algorithm based on inductive transfer learning .

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。

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 .

之前也有很多研究将迁移学习应用到推荐系统中来改进推荐系统，但是之前的研究都是迁移推荐系统中的用户评分矩阵，而且这些研究工作都要求源领域中的评分数据足够密集。

Many previous works have applied transfer learning to recommender systems to solve the cold start and rating sparsity problems . Most of these applications transfer user-item rating patterns . However , these applications require that the rating data on the auxiliary domain should be dense enough .

利用IBMAGLET平台的相关工具实现了基于移动Agent技术的电子商务系统有关Agent的动态迁移、学习Agent及平台无关性：等关键技术。

In the use of the IBM Aglet platform and tools , we realize the key technologies based on mobile Agent such as the Agent dynamic migration , the study of Agent and the platform independence .

迁移是学习过程的一个重要方面。

The migration is an important aspect of learning process .

许多教育学家、心理学家经过研究后发现，学习迁移是学习中一种普遍现象，凡是有学习的地方几乎就有迁移的发生。

Many educators , psychologists found that transport is a universal phenomenon in the study .

此外，我们还分析讨论了不同特征在迁移排序学习过程中所起的作用。

Furthermore , we analyze and discuss how different features act in the learning process .

教师是学习者，学生学习和迁移的学习原理同样适用与教师。

Teachers are learners and the principles of learning and transfer for student learners apply to teachers .

迁移是学习的一种普遍现象，且已成为教育的基本目标之一。

Transfer , which has already been one basic aim of education , is a common phenomenon in learning .

引入了迁移与学习算子，以提高遗传算法的有效性与收敛性。

In order to enhance the validity and convergence of the genetic algorithm , the learning and migration operators are introduced .

浅谈语文教学中知识的迁移与学习的延伸从不同的方向无意的延伸（好像漫游一样）。

Of the changing of knowledge and extension of study in Chinese language teaching ; spreading out carelessly ( as if wandering ) in different directions .