Influence Maximization (IM), that seeks a small set of key users who spread the influence widely into network, is core problem in multiple domains. It finds applications viral marketing, epidemic control, and assessing cascading failures within complex systems. Despite huge amount effort, IM billion-scale networks such as Facebook, Twitter, World Wide Web has not been satisfactorily solved. Even state-of-the-art methods TIM+ IMM may take days on those networks. In this paper, we propose SSA...

Federated learning has emerged recently as a promising solution for distributing machine tasks through modern networks of mobile devices. Recent studies have obtained lower bounds on the expected decrease in model loss that is achieved each round federated learning. However, convergence generally requires large number communication rounds, which induces delay training and costly terms network resources. In this paper, we propose fast-convergent algorithm, called <inline-formula...

Online social networks have been one of the most effective platforms for marketing and advertising. Through "world-of-mouth" exchanges, so-called viral marketing, influence product adoption can spread from few key influencers to billions users in network. To identify those influencers, a great amount work has devoted Influence Maximization (IM) problem that seeks set k seed maximize expected influence. Unfortunately, IM encloses two impractical assumptions: 1) any user be acquired with same...

Online social networks have been one of the most effective platforms for marketing and advertising. Through “world-of-mouth” exchanges, so-called viral marketing, influence product adoption can spread from few key influencers to billions users in network. To identify those influencers, a great amount work has devoted maximization (IM) problem that seeks set k seed maximize expected influence. Unfortunately, IM encloses two impractical assumptions: 1) any user be acquired with same cost 2)...

Monitoring the health of gearboxes has become necessary in manufacturing field, as unnoticed defects can result significant interruptions and expensive periods inactivity. Vibration diagnostics is a technique used to analyze vibration measured on gearbox housing detect internal fault symptoms. To identify these defects, it continuously record vibrations over long period time with high sample frequency. Consequently, essential have powerful computational capabilities for analyzing collected...

Influence Maximization (IM), that seeks a small set of key users who spread the influence widely into network, is core problem in multiple domains. It finds applications viral marketing, epidemic control, and assessing cascading failures within complex systems. Despite huge amount effort, IM billion-scale networks such as Facebook, Twitter, World Wide Web has not been satisfactorily solved. Even state-of-the-art methods TIM+ IMM may take days on those networks. In this paper, we propose SSA...

Active Directory (AD) is the default security management system for Windows domain networks. An AD environment naturally describes an attack graph where nodes represent computers/accounts/security groups, and edges existing accesses/known exploits that allow attacker to gain access from one node another. Motivated by practical use cases, we study a Stackelberg game between defender. There are multiple entry choose there single target (Domain Admin). Every edge has failure rate. The chooses...

Active Directory is the default security management system for Windows domain networks. We study shortest path edge interdiction problem defending style attack graphs. The formulated as a Stackelberg game between one defender and attacker. graph contains destination node multiple entry nodes. attacker's chosen by nature. chooses to block set of edges limited his budget. attacker then picks unblocked path. aims maximize expected length attacker, where expectation taken over observe that...

Estimating cascade size and nodes' influence is a fundamental task in social, technological, biological networks. Yet this extremely challenging due to the sheer structural heterogeneity of We investigate new measure, termed outward (OI), defined as (expected) number nodes that subset S will activate, excluding S. Thus, OI equals, de facto standard spread minus |S|. not only more informative for with small influence, but also, critical designing effective sampling statistical estimation...

Cyber-epidemics, the widespread of fake news or propaganda through social media, can cause devastating economic and political consequences. A common countermeasure against cyber-epidemics is to disable a small subset suspected connections accounts effectively contain epidemics. An example recent shutdown 125,000 ISIS-related Twitter accounts. Despite many proposed methods identify such subset, none are scalable enough provide high-quality solutions in nowadays' billion-size networks. To this...

The blooming availability of traces for social, biological, and communication networks opens up unprecedented opportunities in analyzing diffusion processes networks. However, the sheer sizes nowadays raise serious challenges computational efficiency scalability. In this paper, we propose a new hyper-graph sketching framework influence dynamics core our framework, called SKIS, is an efficient importance sampling algorithm that returns only non-singular reverse cascades network. Comparing to...

This paper addresses the mathematical modeling of information as originally expressed in natural language conditional form. A number different event algebras—all avoiding Lewis triviality result—are briefly surveyed, including main body those proposed previously, classified Type I, and newly expanded II product space approach (PS) independently offered by Van Fraasen. The issue higher order conditionals is also discussed. In addition, this work considers two basic results McGee: Firstly,...

This paper presents an approach integrating explainable artificial intelligence (XAI) techniques with adaptive learning to enhance energy consumption prediction models, a focus on handling data distribution shifts. Leveraging SHAP clustering, our method provides interpretable explanations for model predictions and uses these insights adaptively refine the model, balancing complexity predictive performance. We introduce three-stage process: (1) obtaining values explain predictions, (2)...

The formal concept of logical equivalence in fuzzy logic, while theoretically sound, seems impractical. misinterpretation this has led to some pessimistic conclusions. Motivated by practical interpretation truth values for propositions, we take the class (lattice) all subintervals unit interval [0, 1] as value space subsuming traditional numerical from 1]. associated is stronger than one. Technically, are dealing with much smaller set pairs equivalent formulas, so that able check...

Estimating cascade size and nodes' influence is a fundamental task in social, technological, biological networks. Yet this extremely challenging due to the sheer structural heterogeneity of We investigate new measure, termed outward (OI), defined as (expected) number nodes that subset S will activate, excluding . Thus, OI equals, de facto standard spread minus | |. not only more informative for with small influence, but also, critical designing effective sampling statistical estimation...

Community detection has emerged rapidly as an important problem for many years. Although a large number of methods this have been proposed, none them address directly the multiplex Online Social Networks (OSNs) in which user can multiple accounts different networks. In paper, we propose and compare two classes approaches named Unifying Approach Coupling community OSNs. Moreover, develop each class specialized NMF-based algorithm. For testing purposes, extend LFR benchmark to generate Our...

The massive explosion of Online Social Networks (OSNs) has brought both great opportunities and security threats. As one the richest sources on personal information, intelligent attackers have actively used OSNs for target reconnaissance in which sensitive information specific users organizations are gathered later attacks. Modeling investigating attackers' techniques is crucial prevention countermeasure cyber-targeted In this paper, we rigorously model closed-wall (e.g. Facebook) using...

This paper addresses mathematical aspects of fuzzy logic. The main results obtained in this are: 1. the introduction a concept normal form logic using hedges; 2. Kolmogorov’s theorem, we prove that all logical operations have forms; 3. for min-max operators, obtain an approximation result similar to universal property neural networks.