Adopting reasonable strategies is challenging but crucial for an intelligent agent with limited resources working in hazardous, unstructured, and dynamic environments to improve the system's utility, decrease the overall cost, and increase mission ...

A strategy refers to the rules that the agent chooses the available actions to achieve goals. Adopting reasonable strategies is challenging but crucial for an intelligent agent with limited resources working in hazardous, unstructured, and dynamic ...

Due to the presence of noise in crowdsourced labels, label aggregation (LA) has become a standard procedure for post-processing these labels. LA methods estimate true labels from crowdsourced labels by modeling worker quality. However, most existing LA ...

In dynamic and resource-constrained Tactical Edge Network (TEN) environments, where Denied, Disrupted, Intermittent, and Limited Impact (DDIL) conditions prevail, a tailored security approach is vital for real-time decision-making. In this paper, we ...

Desalination plants, heavily reliant on Industrial Control Systems (ICS), have emerged as increasingly vital resources in the wake of escalating global water scarcity. This raises an urgent need to prioritize their security, calling for the ...

The issue of structure learning in large Bayesian networks has gained significant attention from the academic community in recent years due to its wide-ranging applications in various fields. Efficient algorithms for structure learning are crucial for ...

This paper assesses the relation between personality, demographics, and learning style. Hence, data is collected from 200 participants using 1) the BFI-10 to obtain the participant’s expression of personality traits according to the five-factor model, 2)...

Bayesian networks (BNs) are attractive, because they are graphical and interpretable machine learning models. However, exact inference on BNs is time-consuming, especially for complex problems. To improve the efficiency, we propose a fast BN exact ...

Critical applications deployed on cloud and in-house information technology infrastructures use software solutions known as high-availability clusters (HACs) to ensure higher availability. Our paper introduces a Bayesian prognostic (BP) framework that ...

Module networks (MoNets) are a parameter-sharing specialization of Bayesian networks that are used for reasoning about multi-dimensional entities with concerted interactions between groups of variables. Construction of MoNets is compute-intensive, with ...

Modern Code Review (MCR) is the process of reviewing new code changes that need to be merged with an existing codebase. As a developer, one may receive many code review requests every day, i.e., the review requests need to be prioritised. Manually ...

Background: The literature presents distinct models to assess the Teamwork Quality (TWQ) for agile teams. These models have different constructs and, consequently, measures. Unfortunately, there are no results of empirical studies contrasting the ...

This paper develops a new approach to learning high-dimensional linear structural equation models (SEMs) without the commonly assumed faithfulness, Gaussian error distribution, and equal error distribution conditions. A key component of the algorithm is ...

To evaluate the quality of open source software ecosystems (OSSECOs) we designed the QuESo-process. This process describes the activities and tasks that support the evaluation of OSSECOs. Our proposal attempts to fill the gap between quality models and ...

Bayesian networks (BNs) are a widely used graphical model in machine learning. As learning the structure of BNs is NP-hard, high-performance computing methods are necessary for constructing large-scale networks. In this paper, we present a parallel ...

We develop ancestral Gumbel-Top-k sampling: a generic and efficient method for sampling without replacement from discrete-valued Bayesian networks, which includes multivariate discrete distributions, Markov chains and sequence models. The method uses an ...

With the deployments of fifth generation mobile networks (5G), rapid development of mobile internet, continued growth in mobile traffic and increased adoption of the internet of things, Multi-access Edge Computing (MEC) remains an inevitable critical ...

Topic modeling has been widely applied in a variety of industrial applications. Training a high-quality model usually requires massive amount of in-domain data, in order to provide comprehensive co-occurrence information for the model to learn. However, ...

Interactive information retrieval (IIR) researchers often conduct laboratory studies to understand the relationship between people seeking information and information retrieval systems. They develop extensive data collection methods and tools create new ...

The incidence of false alerts in the hospital environment compromises the tasks of healthcare professionals, since they: (i) stress the teams of caregivers, and the patients themselves; (ii) may lead to an increase in the length of hospitalization; (iii)...