5 papers · 1 filter
Distributed Resource Selection for Self-Organising Cloud-Edge Systems
Quentin Renau, Amjad Ullah, Emma Hart
This paper presents a distributed resource selection mechanism for diverse cloud-edge environments, enabling dynamic and context-aware allocation of resources to meet the demands o…
Class Incremental Learning for Algorithm Selection
Mate Botond Nemeth, Emma Hart, Kevin Sim +1
Algorithm selection is commonly used to predict the best solver from a portfolio per per-instance. In many real scenarios, instances arrive in a stream: new instances become availa…
A Paired Autoencoder Framework for Inverse Problems via Bayes Risk Minimization
Emma Hart, Julianne Chung, Matthias Chung
In this work, we describe a new data-driven approach for inverse problems that exploits technologies from machine learning, in particular autoencoder network structures. We conside…
Algorithm Selection with Probing Trajectories: Benchmarking the Choice of Classifier Model
Quentin Renau, Emma Hart
Recent approaches to training algorithm selectors in the black-box optimisation domain have advocated for the use of training data that is algorithm-centric in order to encapsulate…
Beyond the Hype: Benchmarking LLM-Evolved Heuristics for Bin Packing
Kevin Sim, Quentin Renau, Emma Hart
Coupling Large Language Models (LLMs) with Evolutionary Algorithms has recently shown significant promise as a technique to design new heuristics that outperform existing methods,…