16 citations · 25 across the 10 of their papers we have counts for
10 papers
Vibe Visualizing: How Visualization Novices Try (and Fail) to Generate and Interpret Visualizations with Conversational AI
Sam Yu-Te Lee, Yun-Hsin Kuo, Chifang Chou +3
Conversational AI has enabled users to generate and interpret visualizations through natural language, significantly lowering the technical barrier to entry. The increased accessib…
Understanding Large-Scale HPC System Behavior Through Cluster-Based Visual Analytics
Allison Austin, Shilpika, Yan To Linus Lam +4
In high-performance computing (HPC) environments, system monitoring data is often unlabeled and high-dimensional, making it difficult to reliably detect and understand anomalous co…
Navigating High-Dimensional Backstage: A Guide for Exploring Literature for the Reliable Use of Dimensionality Reduction
Hyeon Jeon, Hyunwook Lee, Yun-Hsin Kuo +6
Visual analytics using dimensionality reduction (DR) can easily be unreliable for various reasons, e.g., inherent distortions in representing the original data. The literature has…
Unveiling High-dimensional Backstage: A Survey for Reliable Visual Analytics with Dimensionality Reduction
Hyeon Jeon, Hyunwook Lee, Yun-Hsin Kuo +6
Dimensionality reduction (DR) techniques are essential for visually analyzing high-dimensional data. However, visual analytics using DR often face unreliability, stemming from fact…
SpreadLine: Visualizing Egocentric Dynamic Influence
Yun-Hsin Kuo, Dongyu Liu, Kwan-Liu Ma
Egocentric networks, often visualized as node-link diagrams, portray the complex relationship (link) dynamics between an entity (node) and others. However, common analytics tasks a…
VisActs: Describing Intent in Communicative Visualization
Keshav Dasu, Yun-Hsin Kuo, Kwan-Liu Ma
Data visualization can be defined as the visual communication of information. One important barometer for the success of a visualization is whether the intents of the communicator(…
Character-Oriented Design for Visual Data Storytelling
Keshav Dasu, Yun-Hsin Kuo, Kwan-Liu Ma
When telling a data story, an author has an intention they seek to convey to an audience. This intention can be of many forms such as to persuade, to educate, to inform, or even to…
Classes are not Clusters: Improving Label-based Evaluation of Dimensionality Reduction
Hyeon Jeon, Yun-Hsin Kuo, Michaël Aupetit +2
A common way to evaluate the reliability of dimensionality reduction (DR) embeddings is to quantify how well labeled classes form compact, mutually separated clusters in the embedd…
Feature Learning for Nonlinear Dimensionality Reduction toward Maximal Extraction of Hidden Patterns
Takanori Fujiwara, Yun-Hsin Kuo, Anders Ynnerman +1
Dimensionality reduction (DR) plays a vital role in the visual analysis of high-dimensional data. One main aim of DR is to reveal hidden patterns that lie on intrinsic low-dimensio…
A Machine-Learning-Aided Visual Analysis Workflow for Investigating Air Pollution Data
Yun-Hsin Kuo, Takanori Fujiwara, Charles C. -K. Chou +2
Analyzing air pollution data is challenging as there are various analysis focuses from different aspects: feature (what), space (where), and time (when). As in most geospatial anal…