Other industries also use adaptive algorithms to provide better results, improving services for consumers and generating more revenue. A good example of this is in traffic navigation apps such as ...

Bias in adaptive learning algorithms can originate from different sources, such as the data, the model, the context, or the user. For example, the data used to train or evaluate the algorithm ...

Learn from successful examples of adaptive learning evaluation in teaching, and discover how to measure and compare learning outcomes, experience, efficiency, and impact.

This repository contains the source code of KADABRA, an adaptive probabilistic algorithm for approximating the betweenness centrality of nodes in a network. The algorithm is presented in the paper ...

This paper presents a detailed analysis of the algorithm performances, including procedures and relations that can be used for a fine adjustment of the algorithm parameters. Reliability of the ...

In this work, we investigate an active learning approach for ICL, where there is a limited budget for annotating examples. We propose a model-adaptive optimization-free algorithm, termed AdaICL, which ...

This includes those using artificial intelligence with fixed or adaptive algorithms. Examples include types of radiotherapy, implanted neuromodulators, and apps or software used to deliver cognitive ...

Abstract: An adaptive k-nearest neighbor algorithm (AdaNN) is brought forward in this paper to overcome the limitation of the traditional k-nearest neighbor algorithm (kNN) which usually identifies ...