102 citations · 738 across the 28 of their papers we have counts for
28 papers
Enhancing AIGC Service Efficiency with Adaptive Multi-Edge Collaboration in A Distributed System
Changfu Xu, Jianxiong Guo, Jiandian Zeng +4
The Artificial Intelligence Generated Content (AIGC) technique has gained significant traction for producing diverse content. However, existing AIGC services typically operate with…
A Fast Task Offloading Optimization Framework for IRS-Assisted Multi-Access Edge Computing System
Jianqiu Wu, Zhongyi Yu, Jianxiong Guo +3
Terahertz communication networks and intelligent reflecting surfaces exhibit significant potential in advancing wireless networks, particularly within the domain of aerial-based mu…
An Online Resource Scheduling for Maximizing Quality-of-Experience in Meta Computing
Yandi Li, Jianxiong Guo, Yupeng Li +2
Meta Computing is a new computing paradigm, which aims to solve the problem of computing islands in current edge computing paradigms and integrate all the resources on a network by…
Multi-Task Diffusion Incentive Design for Mobile Crowdsourcing in Social Networks
Jianxiong Guo, Qiufen Ni, Weili Wu +1
Mobile Crowdsourcing (MCS) is a novel distributed computing paradigm that recruits skilled workers to perform location-dependent tasks. A number of mature incentive mechanisms have…
MTMD: Multi-Scale Temporal Memory Learning and Efficient Debiasing Framework for Stock Trend Forecasting
Mingjie Wang, Juanxi Tian, Mingze Zhang +2
The endeavor of stock trend forecasting is principally focused on predicting the future trajectory of the stock market, utilizing either manual or technical methodologies to optimi…
A Survey on Influence Maximization: From an ML-Based Combinatorial Optimization
Yandi Li, Haobo Gao, Yunxuan Gao +2
Influence Maximization (IM) is a classical combinatorial optimization problem, which can be widely used in mobile networks, social computing, and recommendation systems. It aims at…
FedCL: Federated Multi-Phase Curriculum Learning to Synchronously Correlate User Heterogeneity
Mingjie Wang, Jianxiong Guo, Weijia Jia
Federated Learning (FL) is a decentralized learning method used to train machine learning algorithms. In FL, a global model iteratively collects the parameters of local models with…
ToupleGDD: A Fine-Designed Solution of Influence Maximization by Deep Reinforcement Learning
Tiantian Chen, Siwen Yan, Jianxiong Guo +1
Aiming at selecting a small subset of nodes with maximum influence on networks, the Influence Maximization (IM) problem has been extensively studied. Since it is #P-hard to compute…
Composite Community-Aware Diversified Influence Maximization with Efficient Approximation
Jianxiong Guo, Qiufen Ni, Weili Wu +1
Influence Maximization (IM) is a famous topic in mobile networks and social computing, which aims at finding a small subset of users to maximize the influence spread through online…
Graph Representation Learning for Popularity Prediction Problem: A Survey
Tiantian Chen, Jianxiong Guo, Weili Wu
The online social platforms, like Twitter, Facebook, LinkedIn and WeChat, have grown really fast in last decade and have been one of the most effective platforms for people to comm…
Combinatorial Resources Auction in Decentralized Edge-Thing Systems Using Blockchain and Differential Privacy
Jianxiong Guo, Xingjian Ding, Weijia Jia
With the continuous expansion of Internet of Things (IoT) devices, edge computing mode has emerged in recent years to overcome the shortcomings of traditional cloud computing mode,…
Differential Privacy-Based Online Allocations towards Integrating Blockchain and Edge Computing
Jianxiong Guo, Weili Wu
In recent years, the blockchain-based Internet of Things (IoT) has been researched and applied widely, where each IoT device can act as a node in the blockchain. However, these lig…
A Double Auction for Charging Scheduling among Vehicles Using DAG-Blockchains
Jianxiong Guo, Xingjian Ding, Weili Wu +1
Electric Vehicles (EVs) are becoming more and more popular in our daily life, which replaces traditional fuel vehicles to reduce carbon emissions and protect the environment. EVs n…
Pricing and Budget Allocation for IoT Blockchain with Edge Computing
Xingjian Ding, Jianxiong Guo, Deying Li +1
Attracted by the inherent security and privacy protection of the blockchain, incorporating blockchain into Internet of Things (IoT) has been widely studied in these years. However,…
Reliable Traffic Monitoring Mechanisms Based on Blockchain in Vehicular Networks
Jianxiong Guo, Xingjian Ding, Weili Wu
The real-time traffic monitoring is a fundamental mission in a smart city to understand traffic conditions and avoid dangerous incidents. In this paper, we propose a reliable and e…
Overall Evaluations on Benefits of Influence When Disturbed by Rivals
Jianxiong Guo, Yapu Zhang, Weili Wu
Influence maximization (IM) is a representative and classic problem that has been studied extensively before. The most important application derived from the IM problem is viral ma…
Adaptive Multi-Feature Budgeted Profit Maximization in Social Networks
Tiantian Chen, Jianxiong Guo, Weili Wu
Online social network has been one of the most important platforms for viral marketing. Most of existing researches about diffusion of adoptions of new products on networks are abo…
An Architecture for Distributed Energies Trading in Byzantine-Based Blockchain
Jianxiong Guo, Xingjian Ding, Weili Wu
With the development of smart cities, not only are all corners of the city connected to each other, but also connected from city to city. They form a large distributed network toge…
Adaptive Influence Maximization: If Influential Node Unwilling to Be the Seed
Jianxiong Guo, Weili Wu
Influence maximization problem attempts to find a small subset of nodes that makes the expected influence spread maximized, which has been researched intensively before. They all a…
Continuous Profit Maximization: A Study of Unconstrained Dr-submodular Maximization
Jianxiong Guo, Weili Wu
Profit maximization (PM) is to select a subset of users as seeds for viral marketing in online social networks, which balances between the cost and the profit from influence spread…
A k-hop Collaborate Game Model: Extended to Community Budgets and Adaptive Non-Submodularity
Jianxiong Guo, Weili Wu
Revenue maximization (RM) is one of the most important problems on online social networks (OSNs), which attempts to find a small subset of users in OSNs that makes the expected rev…
Attract More Miners to Join in Blochchain Construction for Internet of Things
Xingjian Ding, Jianxiong Guo, Deying Li +1
The world-changing blockchain technique provides a novel method to establish a secure, trusted and decentralized system for solving the security and personal privacy problems in In…
Continuous Activity Maximization in Online Social Networks
Jianxiong Guo, Tiantian Chen, Weili Wu
Activity maximization is a task of seeking a small subset of users in a given social network that makes the expected total activity benefit maximized. This is a generalization of m…
Combined Cooling, Heating, and Power System in Blockchain-Enabled Energy Management
Jianxiong Guo, Xingjian Ding, Weili Wu
The combined cooling, heating and power (CCHP) system is a typical distributed, electricity-gas integrated energy scheme in a community. First, it generates electricity by use of g…