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区块链技术：架构及进展 - ict.ac.cn

2017 CHINESE JOURNAL OF COMPUTERS 2017 Online (2012CB316203) (61432006,61370101) (172102310714,172102210593) (15A520112) . , ,1976 , , , ,1977 , , , , , ,1977 , , , , . , ,1976 , , , Web . , ,1965 , , , , , Web . 1) ,2) 1) 1) 1) 1) 1)( , 200062) 2)( , 450007) Hyperledger Fabric

blockchain scalability is analyzed about sharding and multichannel, blockchain security is discussed from digital signing and verification, and privacy preserving. This paper also analyzes the advantages, disadvantages and technology trends of blockchain by comparing with traditional databases, and gives several challenging research

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Transcription of 区块链技术：架构及进展 - ict.ac.cn

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基于深度学习的推荐系统研究综述 - ict.ac.cn

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(Beijing Institute of Remote Sensing, Beijing . 100192) 2) (D. epartment of Computer Science and Technology, Tsinghua University, Beijing 100084) Abstract. With the ever-growing volume, complexity and dynamicity of online information, recommender

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DCTCP, and the most suitable traffic control algorithm for RDMA data center is DCQCN. Other researches require expensive custom hardware, which is difficult to deploy. (2) The traffic control technology is a technology of fair utilization of limited resources. Therefore, the performance of the technology can be improved

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A Deep Reinforcement Learning-BasedDistributed Service Offloading Method ... average service latency by 0.4% to 20.4% compared with four exiting service offloading methods in different IoV environments, proving the effectiveness and efficiency of D-SOAC. ... asynchronous advantage actor-critic 1 引言 ...

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深度强化学习综述 - ict.ac.cn

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optimization methods to optimize the policies. In this part, we firstly highlight some pure policy gradient methods, then focus on a series of policy-based DRL algorithms which use the actor-critic framework e.g., Deep Deterministic Policy Gradient (DDPG), followed by an effective method named Asynchronous Advantage

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生成对抗网络及其在图像生成中的 ... - ict.ac.cn

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and computational challenges. At the same time, generative adversarial networks are the latest and most successful technology among generative models. Especially in terms of image generation, compared with other generation models, generative adversarial networks can not only avoid complicated calculations, but also generate better quality images.

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脉冲神经网络研究现状及展望 - ict.ac.cn

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