## Search

Now showing items 1-10 of 324

#### A revisited branch-and-cut algorithm for large-scale orienteering problems

(2024-02-16)

The orienteering problem is a route optimization problem which consists of finding a simple cycle that maximizes the total collected profit subject to a maximum distance limitation. In the last few decades, the occurrence ...

#### Spatio‑temporal modelling of high‑throughput phenotyping data

(2023-10-13)

High throughput phenotyping (HTP) platforms and devices are increasingly used to characterise growth and developmental processes for large sets of plant genotypes. This dissertation is motivated by the need to accurately ...

#### Supervised Learning in Time-dependent Environments with Performance Guarantees

(2023-09-25)

In practical scenarios, it is common to learn from a sequence of related problems (tasks).
Such tasks are usually time-dependent in the sense that consecutive tasks are often
significantly more similar. Time-dependency ...

#### Derivative curve estimation in longitudinal studies using P-splines

(2023-09-18)

The estimation of curve derivatives is of interest in many disciplines. It allows the extraction of important characteristics to gain insight about the underlying process. In the context of longitudinal data, the derivative ...

#### Efficient Learning of Minimax Risk Classifiers in High Dimensions

(2023-08-01)

High-dimensional data is common in multiple areas, such as health care and genomics, where the
number of features can be tens of thousands. In
such scenarios, the large number of features often leads to inefficient ...

#### New Knowledge about the Elementary Landscape Decomposition for Solving the Quadratic Assignment Problem

(2023-07-15)

Previous works have shown that studying the characteristics of the Quadratic Assignment Problem (QAP) is a crucial step in gaining knowledge that can be used to design tailored meta-heuristic algorithms. One way to analyze ...

#### Minimax Risk Classifiers with 0-1 Loss

(2023-07-01)

Supervised classification techniques use training samples to learn a classification rule with
small expected 0 -1 loss (error probability). Conventional methods enable tractable learning
and provide out-of-sample ...

#### Competing risk modelling for in-hospital length of stay

(2023-07)

In this study, we propose a framework for analysing in-hospital patient data from electronic health records. We transform longitudinal sparse vital signs measurements into cross-sectional data via descriptive statistics, ...

#### On the utilization of pair-potential energy functions in multi-objective optimization

(2023-06-01)

In evolutionary multi-objective optimization (EMO), the pair-potential energy functions (PPFs) have been used to construct diversity-preserving mechanisms to improve Pareto front approximations. Despite PPFs have shown ...

#### Competing risk models in early warning systems for in-hospital deterioration: the role of missing data imputation

(2023-06)

Early Warning Systems (EWS) are useful and very important tools for evaluating the health deteriorating of hospitalised patients, using vital signs (such as heart rate, temperature, etc.) as the main input, based on ...