OpenGL Superbible Comprehensive Tutorial and Reference(7th) 英文epub 第7版 本资源转载自网络，如有侵权，请联系上传者或csdn删除 本资源转载自网络，如有侵权，请联系上传者或csdn删除

SAP Process Orchestration (SAP PO) The Comprehensive Guide(2nd) 英文epub 第2版 本资源转载自网络，如有侵权，请联系上传者或csdn删除 查看此书详细信息请在美国亚马逊官网搜索此书

The TCPIP Guide A Comprehensive, Illustrated Internet Protocols Reference 英文无水印pdf pdf所有页面使用FoxitReader和PDF-XChangeViewer测试都可以打开 本资源转载自网络，如有侵权，请联系上传者或csdn删除 本资源转载自网络，如有侵权，请联系上传者或csdn删除

Abstract—Transfer learning aims at improving the performance of target learners on target domains by transferring the knowledge contained in different but related source domains. In this way, the dependence on a large number of target domain data can be reduced for constructing target learners. Due to the wide application prospects, transfer learning has become a popular and promising area in machine learning. Although there are already some valuable and impressive surveys on transfer learning, these surveys introduce approaches in a relatively isolated way and lack the recent advances in transfer learning. As the rapid expansion of the transfer learning area, it is both necessary and challenging to comprehensively review the relevant studies. This survey attempts to connect and systematize the existing transfer learning researches, as well as to summarize and interpret the mechanisms and the strategies in a comprehensive way, which may help readers have a better understanding of the current research status and ideas. Different from previous surveys, this survey paper reviews over forty representative transfer learning approaches from the perspectives of data and model. The applications of transfer learning are also briefly introduced. In order to show the performance of different transfer learning models, twenty representative transfer learning models are used for experiments. The models are performed on three different datasets, i.e., Amazon Reviews, Reuters-21578, and Office-31. And the experimental results demonstrate the importance of selecting appropriate transfer learning models for different applications in practice.

作为一种比传统机器学习方法更有效的训练框架，元学习获得了广泛的欢迎。然而，在多模态任务等复杂任务分布中，其泛化能力尚未得到深入研究。近年来，基于多模态的元学习出现了一些研究。本综述从方法论和应用方面提供了基于多模态的元学习景观的全面概述。我们首先对元学习和多模态的定义进行了形式化的界定，并提出了这一新兴领域的研究挑战，如何丰富少样本或零样本情况下的输入，以及如何将模型泛化到新的任务中。然后我们提出了一个新的分类系统，系统地讨论了结合多模态任务的典型元学习算法。我们对相关论文的贡献进行了调研，并对其进行了分类总结。最后，提出了该领域的研究方向。

A very good textbook for researchers working on the NN theory, yet if you just want to know what is NN, it perhaps is too much for you to digest!

Introduction to Java Programming and Data Structures, Comprehensive Version, Global Edition,11ed，梁勇教授（Y.Daniel Liang）最新的教材，第11版，全网独家资源。原版高清pdf，可以打印，非扫描版，内含全部奖励章节。

OpenGL Superbible Comprehensive Tutorial and Reference(7th) 英文无水印pdf 第7版 pdf所有页面使用FoxitReader和PDF-XChangeViewer测试都可以打开 本资源转载自网络，如有侵权，请联系上传者或csdn删除 本资源转载自网络，如有侵权，请联系上传者或csdn删除

RF调试，80-p4471-100

【导读】近年来深度学习芯片的研究发展是业界关注的焦点。专知之前报道过Google AI Jeff Dean独自撰文的关于AI时代芯片的历史发展趋势-【Google Jeff Dean独自署名论文】深度学习革命及其对计算机架构和芯片设计的影响，讲述AI芯片发展历程与未来，但学术业界一直缺乏对当前深度学习编译器框架的综述。最近北航的学者撰写了第一篇关于当下深度学习编译器的综述论文《The Deep Learning Compiler: A Comprehensive Survey》36页pdf1，从各个方面对现有的DL编译器进行了全面的比较。此外，还详细分析了多级红外设计和编译优化技术。最后，指出了DL编译器的研究方向，很好的论文。