Machine Learning and Knowledge Extraction, Volume 4, Issue 1

Reinforcement learning (RL) has become a highly successful framework for learning in Markov decision processes (MDP). Due to the adoption of RL in realistic and complex environments, solution robustness becomes an increasingly important aspect of RL...

Biomedical Named-Entity Recognition (BioNER) has become an essential part of text mining due to the continuously increasing digital archives of biological and medical articles. While there are many well-performing BioNER tools for entities such as ge...

Machine learning (ML) models are increasingly being used for high-stake applications that can greatly impact people’s lives. Sometimes, these models can be biased toward certain social groups on the basis of race, gender, or ethnicity. Many pri...

Arrays of Cholesteric Spherical Reflectors (CSRs), microscopic cholesteric liquid crystals in a spherical shape, have been argued to become a game-changing technology in anti-counterfeiting. Used to build identifiable tags or coating, called CSR IDs,...

Reinforcement learning (RL) allows an agent to solve sequential decision-making problems by interacting with an environment in a trial-and-error fashion. When these environments are very complex, pure random exploration of possible solutions often fa...

Air quality is relevant to society because it poses environmental risks to humans and nature. We use explainable machine learning in air quality research by analyzing model predictions in relation to the underlying training data. The data originate f...

Datasets with thousands of features represent a challenge for many of the existing learning methods because of the well known curse of dimensionality. Not only that, but the presence of irrelevant and redundant features on any dataset can degrade the...

To encourage proper employee scheduling for managing crew load, restaurants need accurate sales forecasting. This paper proposes a case study on many machine learning (ML) models using real-world sales data from a mid-sized restaurant. Trendy recurre...

Rigorous peer-reviews are the basis of high-quality academic publishing [...]

Data-intensive workloads and applications, such as machine learning (ML), are fundamentally limited by traditional computing systems based on the von-Neumann architecture. As data movement operations and energy consumption become key bottlenecks in t...

The amount of information preserved in Portuguese archives has increased over the years. These documents represent a national heritage of high importance, as they portray the country’s history. Currently, most Portuguese archives have made thei...

Transfer learning is a machine learning technique that uses previously acquired knowledge from a source domain to enhance learning in a target domain by reusing learned weights. This technique is ubiquitous because of its great advantages in achievin...

Hybrid simulation is a method used to investigate the dynamic response of a system subjected to a realistic loading scenario. The system under consideration is divided into multiple individual substructures, out of which one or more are tested physic...