Search Results for author: Rongpeng Li

Found 40 papers, 5 papers with code

Adaptive Layer Splitting for Wireless LLM Inference in Edge Computing: A Model-Based Reinforcement Learning Approach

no code implementations3 Jun 2024 Yuxuan Chen, Rongpeng Li, Xiaoxue Yu, Zhifeng Zhao, Honggang Zhang

Optimizing the deployment of large language models (LLMs) in edge computing environments is critical for enhancing privacy and computational efficiency.

Computational Efficiency Edge-computing +1

Snake Learning: A Communication- and Computation-Efficient Distributed Learning Framework for 6G

no code implementations6 May 2024 Xiaoxue Yu, Xingfu Yi, Rongpeng Li, Fei Wang, Chenghui Peng, Zhifeng Zhao, Honggang Zhang

Existing distributed learning frameworks like Federated Learning and Split Learning often struggle with significant challenges in dynamic network environments including high synchronization demands, costly communication overheads, severe computing resource consumption, and data heterogeneity across network nodes.

Federated Learning Language Modelling +1

Topology Data Analysis-based Error Detection for Semantic Image Transmission with Incremental Knowledge-based HARQ

no code implementations18 Mar 2024 Fei Ni, Rongpeng Li, Zhifeng Zhao, Honggang Zhang

In particular, different from the conventional CRC, we introduce a topological data analysis (TDA)-based error detection method, which capably digs out the inner topological and geometric information of images, so as to capture semantic information and determine the necessity for re-transmission.

Semantic Communication Topological Data Analysis

Interplay of Semantic Communication and Knowledge Learning

no code implementations18 Jan 2024 Fei Ni, Bingyan Wang, Rongpeng Li, Zhifeng Zhao, Honggang Zhang

In the swiftly advancing realm of communication technologies, Semantic Communication (SemCom), which emphasizes knowledge understanding and processing, has emerged as a hot topic.

Data Augmentation Knowledge Graphs +1

Multi-Agent Probabilistic Ensembles with Trajectory Sampling for Connected Autonomous Vehicles

no code implementations21 Dec 2023 Ruoqi Wen, Jiahao Huang, Rongpeng Li, Guoru Ding, Zhifeng Zhao

In this study, we try to address the decision-making problem of multiple CAVs with limited communications and propose a decentralized Multi-Agent Probabilistic Ensembles with Trajectory Sampling algorithm MA-PETS.

Autonomous Vehicles Decision Making +2

Noise Distribution Decomposition based Multi-Agent Distributional Reinforcement Learning

no code implementations12 Dec 2023 Wei Geng, Baidi Xiao, Rongpeng Li, Ning Wei, Dong Wang, Zhifeng Zhao

In this paper, we propose a novel decomposition-based multi-agent distributional RL method by approximating the globally shared noisy reward by a Gaussian mixture model (GMM) and decomposing it into the combination of individual distributional local rewards, with which each agent can be updated locally through distributional RL.

Distributional Reinforcement Learning Multi-agent Reinforcement Learning +2

Self-Critical Alternate Learning based Semantic Broadcast Communication

no code implementations3 Dec 2023 Zhilin Lu, Rongpeng Li, Ming Lei, Chan Wang, Zhifeng Zhao, Honggang Zhang

In particular, to enable stable optimization via a nondifferentiable semantic metric, we regard sentence similarity as a reward and formulate this learning process as an RL problem.

Reinforcement Learning (RL) Semantic Communication +4

Imitation Learning based Alternative Multi-Agent Proximal Policy Optimization for Well-Formed Swarm-Oriented Pursuit Avoidance

no code implementations6 Nov 2023 Sizhao Li, Yuming Xiang, Rongpeng Li, Zhifeng Zhao, Honggang Zhang

Multi-Robot System (MRS) has garnered widespread research interest and fostered tremendous interesting applications, especially in cooperative control fields.

Imitation Learning

Alternate Learning based Sparse Semantic Communications for Visual Transmission

no code implementations31 Jul 2023 Siyu Tong, Xiaoxue Yu, Rongpeng Li, Kun Lu, Zhifeng Zhao, Honggang Zhang

Semantic communication (SemCom) demonstrates strong superiority over conventional bit-level accurate transmission, by only attempting to recover the essential semantic information of data.

Quantization Semantic Communication

Select2Col: Leveraging Spatial-Temporal Importance of Semantic Information for Efficient Collaborative Perception

1 code implementation31 Jul 2023 Yuntao Liu, Qian Huang, Rongpeng Li, Xianfu Chen, Zhifeng Zhao, Shuyuan Zhao, Yongdong Zhu, Honggang Zhang

Collaborative perception by leveraging the shared semantic information plays a crucial role in overcoming the individual limitations of isolated agents.

Graph Neural Network

Decentralized Adaptive Formation via Consensus-Oriented Multi-Agent Communication

no code implementations23 Jul 2023 Yuming Xiang, Sizhao Li, Rongpeng Li, Zhifeng Zhao, Honggang Zhang

Adaptive multi-agent formation control, which requires the formation to flexibly adjust along with the quantity variations of agents in a decentralized manner, belongs to one of the most challenging issues in multi-agent systems, especially under communication-limited constraints.

Multi-agent Reinforcement Learning

NetGPT: A Native-AI Network Architecture Beyond Provisioning Personalized Generative Services

no code implementations12 Jul 2023 Yuxuan Chen, Rongpeng Li, Zhifeng Zhao, Chenghui Peng, Jianjun Wu, Ekram Hossain, Honggang Zhang

Towards personalized generative services, a collaborative cloud-edge methodology is promising, as it facilitates the effective orchestration of heterogeneous distributed communication and computing resources.

RHFedMTL: Resource-Aware Hierarchical Federated Multi-Task Learning

no code implementations1 Jun 2023 Xingfu Yi, Rongpeng Li, Chenghui Peng, Fei Wang, Jianjun Wu, Zhifeng Zhao

The rapid development of artificial intelligence (AI) over massive applications including Internet-of-things on cellular network raises the concern of technical challenges such as privacy, heterogeneity and resource efficiency.

Federated Learning Multi-Task Learning

Knowledge Enhanced Semantic Communication Receiver

no code implementations13 Feb 2023 Bingyan Wang, Rongpeng Li, Jianhang Zhu, Zhifeng Zhao, Honggang Zhang

In recent years, with the rapid development of deep learning and natural language processing technologies, semantic communication has become a topic of great interest in the field of communication.

Semantic Communication

Semantics-enhanced Temporal Graph Networks for Content Popularity Prediction

no code implementations29 Jan 2023 Jianhang Zhu, Rongpeng Li, Xianfu Chen, Shiwen Mao, Jianjun Wu, Zhifeng Zhao

On top of that, we customize its temporal and structural learning modules to further boost the prediction performance.

Graph Learning Graph Neural Network

Semantics-Empowered Communication: A Tutorial-cum-Survey

no code implementations16 Dec 2022 Zhilin Lu, Rongpeng Li, Kun Lu, Xianfu Chen, Ekram Hossain, Zhifeng Zhao, Honggang Zhang

Along with the springing up of the semantics-empowered communication (SemCom) research, it is now witnessing an unprecedentedly growing interest towards a wide range of aspects (e. g., theories, applications, metrics and implementations) in both academia and industry.

AoI-based Temporal Attention Graph Neural Network for Popularity Prediction and Content Caching

no code implementations18 Aug 2022 Jianhang Zhu, Rongpeng Li, Guoru Ding, Chan Wang, Jianjun Wu, Zhifeng Zhao, Honggang Zhang

In this paper, to maximize the cache hit rate, we leverage an effective dynamic graph neural network (DGNN) to jointly learn the structural and temporal patterns embedded in the bipartite graph.

Graph Neural Network

Contrastive Monotonic Pixel-Level Modulation

1 code implementation23 Jul 2022 Kun Lu, Rongpeng Li, Honggang Zhang

Continuous one-to-many mapping is a less investigated yet important task in both low-level visions and neural image translation.

Translation

Adaptive Bit Rate Control in Semantic Communication with Incremental Knowledge-based HARQ

no code implementations13 Mar 2022 Qingyang Zhou, Rongpeng Li, Zhifeng Zhao, Yong Xiao, Honggang Zhang

Semantic communication has witnessed a great progress with the development of natural language processing (NLP) and deep learning (DL).

Semantic Communication

Communication-Efficient Consensus Mechanism for Federated Reinforcement Learning

no code implementations30 Jan 2022 Xing Xu, Rongpeng Li, Zhifeng Zhao, Honggang Zhang

The paper considers independent reinforcement learning (IRL) for multi-agent decision-making process in the paradigm of federated learning (FL).

Decision Making Federated Learning +2

Reinforcement Learning-powered Semantic Communication via Semantic Similarity

1 code implementation27 Aug 2021 Kun Lu, Rongpeng Li, Xianfu Chen, Zhifeng Zhao, Honggang Zhang

We introduce a new semantic communication mechanism - SemanticRL, whose key idea is to preserve the semantic information instead of strictly securing the bit-level precision.

reinforcement-learning Reinforcement Learning (RL) +3

Semantic Communication with Adaptive Universal Transformer

no code implementations20 Aug 2021 Qingyang Zhou, Rongpeng Li, Zhifeng Zhao, Chenghui Peng, Honggang Zhang

With the development of deep learning (DL), natural language processing (NLP) makes it possible for us to analyze and understand a large amount of language texts.

Semantic Communication Sentence

Fundamental Limits of Reinforcement Learning in Environment with Endogeneous and Exogeneous Uncertainty

no code implementations15 Jun 2021 Rongpeng Li

Online reinforcement learning (RL) has been widely applied in information processing scenarios, which usually exhibit much uncertainty due to the intrinsic randomness of channels and service demands.

reinforcement-learning Reinforcement Learning (RL)

The Gradient Convergence Bound of Federated Multi-Agent Reinforcement Learning with Efficient Communication

no code implementations24 Mar 2021 Xing Xu, Rongpeng Li, Zhifeng Zhao, Honggang Zhang

The paper considers independent reinforcement learning (IRL) for multi-agent collaborative decision-making in the paradigm of federated learning (FL).

Decision Making Federated Learning +3

Learning to Prune in Training via Dynamic Channel Propagation

1 code implementation3 Jul 2020 Shibo Shen, Rongpeng Li, Zhifeng Zhao, Honggang Zhang, Yugeng Zhou

In this paper, we propose a novel network training mechanism called "dynamic channel propagation" to prune the neural networks during the training period.

KGTK: A Toolkit for Large Knowledge Graph Manipulation and Analysis

1 code implementation29 May 2020 Filip Ilievski, Daniel Garijo, Hans Chalupsky, Naren Teja Divvala, Yixiang Yao, Craig Rogers, Rongpeng Li, Jun Liu, Amandeep Singh, Daniel Schwabe, Pedro Szekely

Knowledge graphs (KGs) have become the preferred technology for representing, sharing and adding knowledge to modern AI applications.

Knowledge Graphs

Stigmergic Independent Reinforcement Learning for Multi-Agent Collaboration

no code implementations28 Nov 2019 Xing Xu, Rongpeng Li, Zhifeng Zhao, Honggang Zhang

With the rapid evolution of wireless mobile devices, there emerges an increased need to design effective collaboration mechanisms between intelligent agents, so as to gradually approach the final collective objective through continuously learning from the environment based on their individual observations.

reinforcement-learning Reinforcement Learning (RL)

Deep Reinforcement Learning with Discrete Normalized Advantage Functions for Resource Management in Network Slicing

no code implementations10 Jun 2019 Chen Qi, Yuxiu Hua, Rongpeng Li, Zhifeng Zhao, Honggang Zhang

Furthermore, as DPGD only works in continuous action space, we embed a k-nearest neighbor algorithm into DQL to quickly find a valid action in the discrete space nearest to the DPGD output.

Management Q-Learning +2

GAN-powered Deep Distributional Reinforcement Learning for Resource Management in Network Slicing

no code implementations10 May 2019 Yuxiu Hua, Rongpeng Li, Zhifeng Zhao, Xianfu Chen, Honggang Zhang

Moreover, we further develop Dueling GAN-DDQN, which uses a specially designed dueling generator, to learn the action-value distribution by estimating the state-value distribution and the action advantage function.

Distributional Reinforcement Learning Generative Adversarial Network +3

Internet of Intelligence: The Collective Advantage for Advancing Communications and Intelligence

no code implementations26 Apr 2019 Rongpeng Li, Zhifeng Zhao, Xing Xu, Fei Ni, Honggang Zhang

Afterwards, we highlight the potential huge impact of CI on both communications and intelligence.

Evaluation Mechanism of Collective Intelligence for Heterogeneous Agents Group

no code implementations1 Mar 2019 Anna Dai, Zhifeng Zhao, Honggang Zhang, Rongpeng Li, Yugeng Zhou

Collective intelligence is manifested when multiple agents coherently work in observation, interaction, decision-making and action.

Decision Making

Brain-Inspired Stigmergy Learning

no code implementations20 Nov 2018 Xing Hsu, Zhifeng Zhao, Rongpeng Li, Honggang Zhang

Stigmergy has proved its great superiority in terms of distributed control, robustness and adaptability, thus being regarded as an ideal solution for large-scale swarm control problems.

Deep Learning with Long Short-Term Memory for Time Series Prediction

no code implementations24 Oct 2018 Yuxiu Hua, Zhifeng Zhao, Rongpeng Li, Xianfu Chen, Zhiming Liu, Honggang Zhang

Time series prediction can be generalized as a process that extracts useful information from historical records and then determines future values.

Time Series Time Series Prediction

AI-based Two-Stage Intrusion Detection for Software Defined IoT Networks

no code implementations7 Jun 2018 Jiaqi Li, Zhifeng Zhao, Rongpeng Li, Honggang Zhang

Software Defined Internet of Things (SD-IoT) Networks profits from centralized management and interactive resource sharing which enhances the efficiency and scalability of IoT applications.

Intrusion Detection Management +1

Deep Reinforcement Learning for Resource Management in Network Slicing

no code implementations17 May 2018 Rongpeng Li, Zhifeng Zhao, Qi Sun, Chi-Lin I, Chenyang Yang, Xianfu Chen, MinJian Zhao, Honggang Zhang

Network slicing is born as an emerging business to operators, by allowing them to sell the customized slices to various tenants at different prices.

Management reinforcement-learning +1

Traffic Prediction Based on Random Connectivity in Deep Learning with Long Short-Term Memory

no code implementations8 Nov 2017 Yuxiu Hua, Zhifeng Zhao, Rongpeng Li, Xianfu Chen, Zhiming Liu, Honggang Zhang

So, the RCLSTM, with certain intrinsic sparsity, have many neural connections absent (distinguished from the full connectivity) and which leads to the reduction of the parameters to be trained and the computational cost.

Traffic Prediction

A Machine Learning Based Intrusion Detection System for Software Defined 5G Network

no code implementations10 Jul 2017 Jiaqi Li, Zhifeng Zhao, Rongpeng Li

As an inevitable trend of future 5G networks, Software Defined architecture has many advantages in providing central- ized control and flexible resource management.

BIG-bench Machine Learning Intrusion Detection +1

The Learning and Prediction of Application-level Traffic Data in Cellular Networks

no code implementations15 Jun 2016 Rongpeng Li, Zhifeng Zhao, Jianchao Zheng, Chengli Mei, Yueming Cai, Honggang Zhang

Afterwards, with the aid of the traffic "big data", we make a comprehensive study over the modeling and prediction framework of cellular network traffic.

Dictionary Learning Traffic Prediction

TACT: A Transfer Actor-Critic Learning Framework for Energy Saving in Cellular Radio Access Networks

no code implementations28 Nov 2012 Rongpeng Li, Zhifeng Zhao, Xianfu Chen, Jacques Palicot, Honggang Zhang

Recent works have validated the possibility of improving energy efficiency in radio access networks (RANs), achieved by dynamically turning on/off some base stations (BSs).

reinforcement-learning Reinforcement Learning (RL)

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