activity
20172023
most citedA Survey on ML4VIS: Applying Machine Learning Advances to Data Visualization

120 citations · 1.5k across the 58 of their papers we have counts for

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Showing 2019Show all

13 papers · 1 filter

cs.HC2019★ 31 cited

sPortfolio: Stratified Visual Analysis of Stock Portfolios

Xuanwu Yue, Jiaxin Bai, Qinhan Liu +4

Quantitative Investment, built on the solid foundation of robust financial theories, is at the center stage in investment industry today. The essence of quantitative investment is…

cs.HC2019★ 9 cited

Visual Analytics of Student Learning Behaviors on K-12 Mathematics E-learning Platforms

Meng Xia, Huan Wei, Min Xu +4

With increasing popularity in online learning, a surge of E-learning platforms have emerged to facilitate education opportunities for k-12 (from kindergarten to 12th grade) student…

cs.HC2019★ 1 cited

CloudDet: Interactive Visual Analysis of Anomalous Performances in Cloud Computing Systems

Ke Xu, Yun Wang, Leni Yang +6

Detecting and analyzing potential anomalous performances in cloud computing systems is essential for avoiding losses to customers and ensuring the efficient operation of the system…

cs.SI2019★ 1 cited

Nonuniform Timeslicing of Dynamic Graphs Based on Visual Complexity

Yong Wang, Daniel Archambault, Hammad Haleem +3

Uniform timeslicing of dynamic graphs has been used due to its convenience and uniformity across the time dimension. However, uniform timeslicing does not take the data set into ac…

cs.LG2019★ 95 cited

Interpretable and Steerable Sequence Learning via Prototypes

Yao Ming, Panpan Xu, Huamin Qu +1

One of the major challenges in machine learning nowadays is to provide predictions with not only high accuracy but also user-friendly explanations. Although in recent years we have…

cs.HC2019★ 42 cited

Narvis: Authoring Narrative Slideshows for Introducing Data Visualization Designs

Qianwen Wang, Zhen Li, Siwei Fu +2

Visual designs can be complex in modern data visualization systems, which poses special challenges for explaining them to the non-experts. However, few if any presentation tools ar…

cs.HC2019★ 94 cited

Towards Automated Infographic Design: Deep Learning-based Auto-Extraction of Extensible Timeline

Chen Zhu-Tian, Yun Wang, Qianwen Wang +2

Designers need to consider not only perceptual effectiveness but also visual styles when creating an infographic. This process can be difficult and time consuming for professional…

cs.HC2019★ 66 cited

LassoNet: Deep Lasso-Selection of 3D Point Clouds

Chen Zhu-Tian, Wei Zeng, Zhiguang Yang +3

Selection is a fundamental task in exploratory analysis and visualization of 3D point clouds. Prior researches on selection methods were developed mainly based on heuristics such a…

cs.CV2019★ 59 cited

EmoCo: Visual Analysis of Emotion Coherence in Presentation Videos

Haipeng Zeng, Xingbo Wang, Aoyu Wu +4

Emotions play a key role in human communication and public presentations. Human emotions are usually expressed through multiple modalities. Therefore, exploring multimodal emotions…

cs.HC2019★ 48 cited

PlanningVis: A Visual Analytics Approach to Production Planning in Smart Factories

Dong Sun, Renfei Huang, Yuanzhe Chen +5

Production planning in the manufacturing industry is crucial for fully utilizing factory resources (e.g., machines, raw materials and workers) and reducing costs. With the advent o…

cs.HC2019

DeepDrawing: A Deep Learning Approach to Graph Drawing

Yong Wang, Zhihua Jin, Qianwen Wang +3

Node-link diagrams are widely used to facilitate network explorations. However, when using a graph drawing technique to visualize networks, users often need to tune different algor…

cs.HC2019★ 4 cited

Learning Vis Tools: Teaching Data Visualization Tutorials

Leo Yu-Ho Lo, Yao Ming, Huamin Qu

Teaching and advocating data visualization are among the most important activities in the visualization community. With growing interest in data analysis from business and science…

cs.LG2019★ 98 cited

ATMSeer: Increasing Transparency and Controllability in Automated Machine Learning

Qianwen Wang, Yao Ming, Zhihua Jin +5

To relieve the pain of manually selecting machine learning algorithms and tuning hyperparameters, automated machine learning (AutoML) methods have been developed to automatically s…