Search Results for author: Lei Lei

Found 11 papers, 1 papers with code

Adapting to Dynamic LEO-B5G Systems: Meta-Critic Learning Based Efficient Resource Scheduling

no code implementations13 Oct 2021 Yaxiong Yuan, Lei Lei, Thang X. Vu, Zheng Chang, Symeon Chatzinotas, Sumei Sun

Low earth orbit (LEO) satellite-assisted communications have been considered as one of key elements in beyond 5G systems to provide wide coverage and cost-efficient data services.

Meta-Learning

Federated Reinforcement Learning: Techniques, Applications, and Open Challenges

no code implementations26 Aug 2021 Jiaju Qi, Qihao Zhou, Lei Lei, Kan Zheng

This paper presents a comprehensive survey of Federated Reinforcement Learning (FRL), an emerging and promising field in Reinforcement Learning (RL).

Edge-computing Federated Learning

An Ensemble Deep Convolutional Neural Network Model for Electricity Theft Detection in Smart Grids

no code implementations10 Feb 2021 Hossein Mohammadi Rouzbahani, Hadis Karimipour, Lei Lei

Smart grids extremely rely on Information and Communications Technology (ICT) and smart meters to control and manage numerous parameters of the network.

Energy Minimization in UAV-Aided Networks: Actor-Critic Learning for Constrained Scheduling Optimization

no code implementations24 Jun 2020 Yaxiong Yuan, Lei Lei, Thang Xuan Vu, Symeon Chatzinotas, Sumei Sun, Bjorn Ottersten

The conventional RL/DRL, e. g., deep Q-learning, however, is limited in dealing with two main issues in constrained combinatorial optimization, i. e., exponentially increasing action space and infeasible actions.

Combinatorial Optimization Q-Learning

Dynamic Energy Dispatch Based on Deep Reinforcement Learning in IoT-Driven Smart Isolated Microgrids

no code implementations7 Feb 2020 Lei Lei, Yue Tan, Glenn Dahlenburg, Wei Xiang, Kan Zheng

Microgrids (MGs) are small, local power grids that can operate independently from the larger utility grid.

Deep Reinforcement Learning for Autonomous Internet of Things: Model, Applications and Challenges

no code implementations22 Jul 2019 Lei Lei, Yue Tan, Kan Zheng, Shiwen Liu, Kuan Zhang, Xuemin, Shen

Next, a comprehensive survey of the state-of-art research on DRL for AIoT is presented, where the existing works are classified and summarized under the umbrella of the proposed general DRL model.

Decision Making

Multi-user Resource Control with Deep Reinforcement Learning in IoT Edge Computing

no code implementations19 Jun 2019 Lei Lei, Huijuan Xu, Xiong Xiong, Kan Zheng, Wei Xiang, Xianbin Wang

By leveraging the concept of mobile edge computing (MEC), massive amount of data generated by a large number of Internet of Things (IoT) devices could be offloaded to MEC server at the edge of wireless network for further computational intensive processing.

Edge-computing

Patent Analytics Based on Feature Vector Space Model: A Case of IoT

no code implementations17 Apr 2019 Lei Lei, Jiaju Qi, Kan Zheng

In order to address the above limitations, we propose a patent analytics based on feature vector space model (FVSM), where the FVSM is constructed by mapping patent documents to feature vectors extracted by convolutional neural networks (CNN).

Information Retrieval

An In-Vehicle KWS System with Multi-Source Fusion for Vehicle Applications

no code implementations12 Feb 2019 Yue Tan, Kan Zheng, Lei Lei

In order to maximize detection precision rate as well as the recall rate, this paper proposes an in-vehicle multi-source fusion scheme in Keyword Spotting (KWS) System for vehicle applications.

General Classification Keyword Spotting

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