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Found 11 papers, 1 papers with code
A Blockchain-empowered Multi-Aggregator Federated Learning Architecture in Edge Computing with Deep Reinforcement Learning Optimization
Moreover, the exploration of FL with multiple aggregators in edge computing is still new in the literature.
Surveying the Landscape of Text Summarization with Deep Learning: A Comprehensive Review
The ability of deep neural networks to learn hierarchical representations of language data, handle variable-length input sequences, and perform well on large datasets makes them well-suited for NLP applications.
A Survey on Influence Maximization: From an ML-Based Combinatorial Optimization
Therefore, we abandon the traditional algorithms based on iterative search and review the recent development of ML-based methods, especially Deep Reinforcement Learning, to solve the IM problem and other variants in social networks.
ToupleGDD: A Fine-Designed Solution of Influence Maximization by Deep Reinforcement Learning
Aiming at selecting a small subset of nodes with maximum influence on networks, the Influence Maximization (IM) problem has been extensively studied.
Graph Representation Learning for Popularity Prediction Problem: A Survey
In this paper, we present a comprehensive review for existing works using GRL methods for popularity prediction problem, and categorize related literatures into two big classes, according to their mainly used model and techniques: embedding-based methods and deep learning methods.
A Random Algorithm for Profit Maximization with Multiple Adoptions in Online Social Networks
Through "word of mouth" effects, information or product adoption could spread from some influential individuals to millions of users in social networks.
Social and Information Networks
Schemes of Propagation Models and Source Estimators for Rumor Source Detection in Online Social Networks: A Short Survey of a Decade of Research
Recent years have seen various rumor diffusion models being assumed in detection of rumor source research of the online social network.
A Double Auction for Charging Scheduling among Vehicles Using DAG-Blockchains
In this process, a constrained multi-item double auction problem is formulated because of the limited charging resources in a CS, which motivates EVs and CSs in this area to participate in the market based on their preferences and statuses.
Networking and Internet Architecture Computer Science and Game Theory
A Blockchain Transaction Graph based Machine Learning Method for Bitcoin Price Prediction
Bitcoin, as one of the most popular cryptocurrency, is recently attracting much attention of investors.
Edge server deployment scheme of blockchain in IoVs
In fact, the application of blockchain in IoVs can be implemented by employing edge computing.
Continuous Profit Maximization: A Study of Unconstrained Dr-submodular Maximization
The objective function of our CPM-MS is dr-submodular, but non-monotone.
