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 …

Inspired by the great success of machine learning (ML), researchers have applied ML
techniques to visualizations to achieve a better design, development, and evaluation of …

The combination of diverse data types and analysis tasks in genomics has resulted in the
development of a wide range of visualization techniques and tools. However, most existing …

Visual analytics systems integrate interactive visualizations and machine learning to enable
expert users to solve complex analysis tasks. Applications combine techniques from various …

Labeled datasets are essential for supervised machine learning. Various data labeling tools
have been built to collect labels in different usage scenarios. However, developing labeling …

In this paper, we present a review of the recent work in deep learning methods for user
interface design. The survey encompasses well known deep learning techniques (deep …

Constructing supervised machine learning models for real-world video analysis require
substantial labeled data, which is costly to acquire due to scarce domain expertise and …

Finding line-chart images similar to a given line-chart image query is a common task in data
exploration and image query systems, eg finding similar trends in stock markets or medical …

Over the past years, an increasing number of publications in information visualization,
especially within the field of visual analytics, have mentioned the term “embedding” when …

Inspired by the great success of machine learning (ML), researchers have applied ML
techniques to visualizations to achieve a better design, development, and evaluation of …