Respondent Driven Sampling study (RDS) is a population sampling method developed to study hard-to-reach populations. A sample is obtained by chain-referral recruitment in a network of contacts within ...

Obtaining information is a crucial part of normal decision-making under uncertainty. For example, deciding where to go out for dinner requires building predictions about how good the food, atmosphere ...

There has been growing attention to multi-class classification problems, particularly those challenges of imbalanced class distributions. To address these challenges, various strategies, including ...

Statistical communication through data visualization is essential across diverse fields, including health, climate, science, education, and policymaking. Despite its widespread use, there is currently ...

Abstract: Trajectory optimization for robotic systems remains a challenging problem. This is especially true for robotic systems featuring nonlinear dynamics and many degrees of freedom. Data-based or ...

Accurate forest volume estimation is crucial for sustainable forest management, but the most commonly used methods often rely on models that may not always be applicable across different tree species ...

Credit rating is a systematic evaluation that assesses the creditworthiness of an individual, corporation, or sovereign entity. It represents a quantitative and qualitative measurement of the ...

Top-p sampling, also called nucleus sampling, is a method used to control how random or focused a model's output is. Instead of picking from all possible next words, it looks at the most likely ones ...