The problem of concept drift has gained a lot of attention in recent years. This aspect is key
in many domains exhibiting non-stationary as well as cyclic patterns and structural breaks …

Recent crises, recessions and bubbles have stressed the non-stationary nature and the
presence of drastic structural changes in the financial domain. The most recent literature …

Surface electromyography (sEMG)-based gesture classification methods have been widely
developed in neural decoding. However, these decoding methods are usually constrained …

When detecting anomalies in audio, it can often be necessary to consider concept drift: the
distribution of the data may drift over time because of dynamically changing environments …

Nowadays, artificial intelligence methods need to face more and more open application
scenarios. They need to have the ability to continuously develop new skills and knowledge …

Catastrophic forgetting challenges lifelong classification learning of modern neural
networks, especially when observations arrive from a data stream and the boundaries of …

Deep learning models have shown impressive performance in various tasks. However, they
are prone to a phenomenon called catastrophic forgetting. This means they do not …

The vibrant Mediterranean city of Barcelona, in Spain, welcomed the 13th edition of WSOM+
2019, the Workshop on Self-Organizing Maps and Learning Vector Quantization, Clustering …

Continual learning aims at developing models that are capable of working on constantly
evolving problems over a long-time horizon. In such environments, we can distinguish three …

A systematic literature review on the formation of human capital through quality education
and lifelong learning is presented in this paper. This article explores the common themes …