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Found 9 papers, 4 papers with code
LBCIM: Loyalty Based Competitive Influence Maximization with epsilon-greedy MCTS strategy
Competitive influence maximization has been studied for several years, and various frameworks have been proposed to model different aspects of information diffusion under the competitive environment.
Screening COVID-19 Based on CT/CXR Images & Building a Publicly Available CT-scan Dataset of COVID-19
Secondly, we propose a deep learning model for screening COVID-19 using our proposed CT dataset and report the baseline results.
DL-Reg: A Deep Learning Regularization Technique using Linear Regression
This linear constraint, which is further adjusted by a regularization factor, prevents the network from the risk of overfitting.
An Efficient Approach For Malware Detection Using PE Header Specification
Following the dramatic growth of malware and the essential role of computer systems in our daily lives, the security of computer systems and the existence of malware detection systems become critical.
Competitive Influence Maximization: Integrating Budget Allocation and Seed Selection
In this work, we integrate these two lines of research and propose a new scenario where competition happens in two phases.
Social and Information Networks Computer Science and Game Theory
Knowledge Representation in Learning Classifier Systems: A Review
To have an elaborated view on the functionality of each technique, a comparative analysis of existing techniques on some conventional problems is provided.
Reducing the Computational Cost in Multi-objective Evolutionary Algorithms by Filtering Worthless Individuals
The large number of exact fitness function evaluations makes evolutionary algorithms to have computational cost.
Using reinforcement learning to find an optimal set of features
Identifying the most characterizing features of observed data is critical for minimizing the classification error.
Using Noun Similarity to Adapt an Acceptability Measure for Persian Light Verb Constructions
In particular, LVCs are formed semi-productively: often a semantically-general verb (such as take) combines with a number of semantically-similar nouns to form semantically-related LVCs, as in make a decision/choice/commitment.
