Search Results (5)
Feature construction techniques in time-series analysis and single-objective optimization
Feature construction, encompassing both feature engineering, which involves the manual design of features by domain experts, and representation learning, which refers to the automated discovery of useful data representations during model construction, is a fundamental aspect of machine learning. Its goal is to transform raw data into a more suitable …
Representing and exploiting benchmarking data for optimisation and learning
The rapid advancements in Machine Learning (ML) and Black-Box Optimization (BBO) have led to an increased reliance on benchmarking data for evaluating and comparing algorithms across diverse domain tasks. However, the effective exploitation of this data is hindered by challenges such as syntactic variability, semantic ambiguity, and lack of standardization. …
Towards understanding the impact of problem landscapes in numerical black-box optimization
In optimization, it is well known that algorithm performance is dependent on the problem being solved. As a consequence of this, achieving good optimization results requires correctly matching an optimization problem to a specific optimization algorithm that performs well on that problem. For this to be possible, knowledge of both …
Development of an alternative approach to membrane protein structure determination based on the analysis of local rotational conformational spaces
The problem of structure determination of membrane proteins is addressed with a new combination of site-directed spin labelling (SDSL) electron paramagnetic resonance (EPR) spectroscopy and structure modelling of a protein and its conformational spaces. This new approach is aimed at structural characterization of membrane proteins and intrinsically disordered proteins. In …
Stigmergy as an Approach to Metaheuristic Optimization
Developing metaheuristics to solve optimization problems is a rapidly growing field of research. This is due to the importance of optimization problems in the scientific as well as the industrial world. The methods developed in this dissertation are based on stigmergy: a method of communication in emergent systems, where the …