Search Results for author: Kan Zheng

Found 9 papers, 0 papers with code

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

LSTM-based Anomaly Detection for Non-linear Dynamical System

no code implementations5 Jun 2020 Yue Tan, Chunjing Hu, Kuan Zhang, Kan Zheng, Ethan A. Davis, Jae Sung Park

Anomaly detection for non-linear dynamical system plays an important role in ensuring the system stability.

Anomaly Detection

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

Short-term Road Traffic Prediction based on Deep Cluster at Large-scale Networks

no code implementations25 Feb 2019 Lingyi Han, Kan Zheng, Long Zhao, Xianbin Wang, Xuemin Shen

Therefore, a framework combining with a deep clustering (DeepCluster) module is developed for STTP at largescale networks in this paper.

Deep Clustering Representation Learning +2

A Driving Intention Prediction Method Based on Hidden Markov Model for Autonomous Driving

no code implementations25 Feb 2019 Shiwen Liu, Kan Zheng, Long Zhao, Pingzhi Fan

Experimental results show that the HMMs trained with the continuous characterization of mobility features can give a higher prediction accuracy when they are used for predicting driving intentions.

Autonomous Driving

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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