… In this paper, we assess the robustness of six state-of-theart deep learning models for AD,
with different levels of training set contamination following our evaluation protocol. These …

… the EVA unsupervised learning model to evaluate the company’… evaluation system based
on the EVA unsupervised learning … evaluation system based on EVA unsupervised learning …

… processed by numerical simulators to evaluate geological uncertainty during the decision-…
In this study, unsupervised machine learning (UML) is applied by considering different (1) …

… As the aim of this study included evaluating the effectiveness of the SAAI system, which
scores students’ constructed responses in unsupervised learning, we collected students’ …

… In this paper, we propose a new federated unsupervised representation learning framework,
FedU, to learn generic … We evaluate the representation learned from FedU using linear …

… for evaluating multidocument summaries, we investigate unsupervised evaluation methods,
which … In particular, we focus on evaluating the relevance (Peyrard, 2019) of multi-document …

… an unsupervised method for evaluating the performance of a clustering method [11]. Since
the Silhouette index does not need a training set to evaluate … index to evaluate the clustering …

… methods, we propose a rigorous evaluation protocol and apply it to … The new evaluation
shows that some methods, previously … We hope that the updated evaluation of anomaly detection …

… This paper studied and analyzed the impact that combinations of unsupervised learning
evaluation metrics have in ranking the members of an energy community and, consequently, on …

… Therefore, this article exposes three unsupervised machine learning models based on
clustering … After evaluation, this paper presents a case of heterogeneous cybersecurity devices, …