Visual analytics for machine learning has recently evolved as one of the most exciting areas
in the field of visualization. To better identify which research topics are promising and to …

Abstract The Electricity Supply Chain is a system of enabling procedures to optimize
processes ranging from production to transportation and consumption of electricity. The …

We present a comprehensive, detailed review of time-series data analysis, with emphasis on
deep time-series clustering (DTSC), and a case study in the context of movement behavior …

In smart manufacturing, people are facing an increasing amount of industrial data derived
from various digitalized and connected sources in all kinds of formats. Analyzing and …

Visualization and artificial intelligence (AI) are well-applied approaches to data analysis. On
one hand, visualization can facilitate humans in data understanding through intuitive visual …

Visual analytics for time series data has received a considerable amount of attention.
Different approaches have been developed to understand the characteristics of the data and …

In this paper, we develop a visual analysis method for interactively improving the quality of
labeled data, which is essential to the success of supervised and semi-supervised learning …

Many real-world datasets are incomplete due to factors such as data collection failures or
misalignments between fused datasets. Visualizations of incomplete datasets should allow …

Federated Edge Learning (FEEL) involves the collaborative training of machine learning
models among edge devices, with the orchestration of a server in a wireless edge network …

In order to effectively infer correct labels from noisy crowdsourced annotations, learning-from-
crowds models have introduced expert validation. However, little research has been done …