transfer learning的例句大全

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.

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。

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

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。

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application of transfer learning law on pharmacology teaching is helpful to improve the quality of teaching, and open up intelligence of medical students.

学习迁移规律在药理学教学中的应用有助于提高教学质量和开拓医学生的智能。

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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.

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。

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This paper also discusses several tricky issues regarding CRFs and transfer learning.

本论文还探讨了CRFs和转移学习中的若干关键点。

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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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application of transfer learning law in pharmacology teaching

论学习迁移规律在药理学教学中的应用

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compared with relearning vocabulary, this transfer learning algorithm makes use of learned knowledge effectively, which can gain good performance especially in the situation when there are a few images in a novel category.

与重新学习视觉词典的分类算法相比，这种迁移算法有效地利用了已有知识，在新类别图像的训练样本较少的情况下，也能获得较好的分类效果。

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

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。

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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.

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。

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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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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.

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。

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

基于迁移学习的自适应室内Wi-Fi定位

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he is also enthusiastic about "open-knowledge" initiatives that transfer learning about development between regions and even cities.

他也热情支持“开放知识”倡议即在不同地区和城市之间传递发展经验。

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the bigger the amount of positive transfer learning is, the stronger the ability of adapting new learning situation and resolving new problems through learning are.

学习的正迁移量越大，说明学生通过学习所产生的适应新的学习情境和解决新的问题的能力越强，学生的学习成绩越好，教学效果就越好。

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then, i used the development of courseware and designed two instructional designs, describing how to train students' ability of transfer learning in the simulation environment.

最后，笔者利用所开发的课件设计了两个教学设计，结合课件具体阐述了仿真实验环境下如何培养学生迁移能力。

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we transfer learning of fcm to optimization problem and imitate the self-organization and self-learning mechanism, the approach of fcm learning is presented based on genetic algorithm.

我们将FCM的学习问题转化为一个优化问题，模拟生物学中的自组织和自学习机制，提出了基于遗传算法的FCM学习和基于免疫遗传算法的FCM学习。

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this paper proposes method of cross-domain network public opinion tendency, which is based on multi-task transfer learning based on markov logic network, design and implement analysis system of public opinion tendency.

通过跨领域知识迁移的分析方法&基于Markov逻辑网的多任务迁移学习，设计并实现了网络舆情倾向性分析系统。

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transfer learning does not require training data and test data subject to the same distribution, but trying to use those old data as much as possible, helping build a new classifier which can have a good performance on new data.

它不要求训练数据与测试数据服从相同分布，而是试图尽量多的去利用那些看起来已经过时的旧数据，帮助少量的新数据去建立一个能够在新数据上有很好表现的分类器。

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

因此，迁移学习不会像传统机器学习那样作同分布假设。

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