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Deep-Reinforcement Learning Multiple Access for Heterogeneous Wireless Networks
This paper investigates the use of deep reinforcement learning (DRL) in ...
12/01/2017 ∙ by Yiding Yu, et al. ∙
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AlphaSeq: Sequence Discovery with Deep Reinforcement Learning
Sequences play an important role in many applications and systems. Disco...
09/26/2018 ∙ by Yulin Shao, et al. ∙
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Carrier-Sense Multiple Access for Heterogeneous Wireless Networks Using Deep Reinforcement Learning
This paper investigates a new class of carrier-sense multiple access (CS...
10/16/2018 ∙ by Yiding Yu, et al. ∙
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Deep Learning for Joint MIMO Detection and Channel Decoding
We propose a deep-learning approach for the joint MIMO detection and cha...
01/17/2019 ∙ by Taotao Wang, et al. ∙
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PubChain: A Decentralized Open-Access Publication Platform with Participants Incentivized by Blockchain Technology
We design and implement Publication Chain (PubChain), a decentralized op...
10/01/2019 ∙ by Taotao Wang, et al. ∙
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Game-Theoretic Analysis of Mining Strategy in Bitcoin-NG Blockchain Protocol
Bitcoin-NG, a scalable blockchain protocol, divides each block into a ke...
11/03/2019 ∙ by Taotao Wang, et al. ∙
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Non-Uniform Time-Step Deep Q-Network for Carrier-Sense Multiple Access in Heterogeneous Wireless Networks
This paper investigates a new class of carrier-sense multiple access (CS...
10/11/2019 ∙ by Yiding Yu, et al. ∙
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When Blockchain Meets AI: Optimal Mining Strategy Achieved By Machine Learning
This work applies reinforcement learning (RL) from the AI machine learni...
11/29/2019 ∙ by Taotao Wang, et al. ∙
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Multi-Agent Deep Reinforcement Learning Multiple Access for Heterogeneous Wireless Networks with Imperfect Channels
This paper investigates a futuristic spectrum sharing paradigm for heter...
03/25/2020 ∙ by Yiding Yu, et al. ∙
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